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Advancements in computation and machine learning have revolutionized science, enabling researchers to address once insurmountable challenges. Bioinformatics, a field that heavily relies on computer-driven analysis of biological data, has greatly benefited from these developments. However, traditional bioinformatics instruction frequently lacks the necessary coding skills. This article explores the transformation of a bioinformatics course in which feedback from students revealed limitations in traditional web application interfaces and the absence of coding automated pipelines for real-world applications. To address these shortcomings, the authors redesigned the project to incorporate computer programming using Google Colaboratory, where students access databases and websites by coding. The curriculum outlined the integration of modern programming skills with essential bioinformatics concepts. This article evaluates the effectiveness of this redesign by analyzing a self-response survey completed by course participants. Results show a positive impact on students' perception of science and scientific research. Bayesian statistical analysis reveals that the programming component significantly predicts students' career clarity in science and their pursuit of graduate education. Integrating coding exercises in bioinformatics education enhances students' preparedness for real-world applications. The freely available GitHub repository will facilitate adoption. By embracing computational tools, students can become adept researchers capable of tackling complex biological questions. [ABSTRACT FROM AUTHOR]

Abstract In the rapidly expanding domain of scientific research, tracking and synthesizing information from the rapidly increasing volume of publications pose significant challenges. To address this, we introduce a novel high-throughput pipeline that employs ChatGPT to systematically extract and analyze connectivity information from the full-texts and abstracts of 24,237 and 150,538 research publications concerning Caenorhabditis elegans and Drosophila melanogaster, respectively. This approach has effectively identified 200,219 and 1,194,587 interactions within the C. elegans and Drosophila biomaps, respectively. Utilizing Cytoscape Web, we have developed a searchable online biomaps that link relevant keywords to their corresponding PubMed IDs, thus providing seamless access to an extensive knowledge network encompassing C. elegans and Drosophila. Our work highlights the transformative potential of integrating artificial intelligence with bioinformatics to deepen our understanding of complex biological systems. By revealing the intricate web of relationships among key entities in C. elegans and Drosophila, we offer invaluable insights that promise to propel advancements in genetics, developmental biology, neuroscience, longevity, and beyond. We also provide details and discuss significant nodes within both biomaps, including the insulin/IGF-1 signaling (IIS) and the notch pathways. Our innovative methodology sets a robust foundation for future research aimed at unravelling complex biological networks across diverse organisms. The two databases are available at worm.bio-map.com and drosophila.bio-map.com.

Online, open access databases for biological knowledge serve as central repositories for research communities to store, find and analyze integrated, multi-disciplinary datasets. With increasing volumes, complexity and the need to integrate genomic, transcriptomic, metabolomic, proteomic, phenomic and environmental data, community databases face tremendous challenges in ongoing maintenance, expansion and upgrades. A common infrastructure framework using community standards shared by many databases can reduce development burden, provide interoperability, ensure use of common standards and support long-term sustainability. Tripal is a mature, open source platform built to meet this need. With ongoing improvement since its first release in 2009, Tripal provides full functionality for searching, browsing, loading and curating numerous types of data and is a primary technology powering at least 31 publicly available databases spanning plants, animals and human data, primarily storing genomics, genetics and breeding data. Tripal software development is managed by a shared, inclusive governance structure including both project management and advisory teams. Here, we report on the most important and innovative aspects of Tripal after 11 years development, including integration of diverse types of biological data, successful collaborative projects across member databases, and support for implementing FAIR principles. [ABSTRACT FROM AUTHOR]

Thrips transmit one of the most devastating plant viruses worldwide–tomato spotted wilt tospovirus (TSWV). Tomato spotted wilt tospovirus is a type species in the genus Orthotospovirus and family Tospoviridae. Although there are more than 7,000 thrips species, only nine thrips species are known to transmit TSWV. In this study, we investigated the molecular factors that could affect thrips ability to transmit TSWV. We assembled transcriptomes of a vector, Frankliniella fusca [Hinds], and a non-vector, Frankliniella tritici [Fitch], and performed qualitative comparisons of contigs associated with virus reception, virus infection, and innate immunity. Annotations of F. fusca and F. tritici contigs revealed slight differences across biological process and molecular functional groups. Comparison of virus cell surface receptors revealed that homologs of integrin were present in both species. However, homologs of another receptor, heperan sulfate, were present in F. fusca alone. Contigs associated with virus replication were identified in both species, but a contig involved in inhibition of virus replication (radical s-adenosylmethionine) was only present in the non-vector, F. tritici. Additionally, some differences in immune signaling pathways were identified between vector and non-vector thrips. Detailed investigations are necessary to functionally characterize these differences between vector and non-vector thrips and assess their relevance in orthotospovirus transmission. [ABSTRACT FROM AUTHOR]

Recent evidence implicates mononuclear diploid cardiomyocytes as a proliferative and regenerative subpopulation of the postnatal heart. The number of these cardiomyocytes is a complex trait showing substantial natural variation among inbred mouse strains based on the combined influences of multiple polymorphic genes. One gene confirmed to influence this parameter is the cardiomyocyte-specific kinase Tnni3k. Here, we have studied Tnni3k alleles across a number of species. Using a newly-generated kinase-dead allele in mice, we show that Tnni3k function is dependent on its kinase activity. In an in vitro kinase assay, we show that several common human TNNI3K kinase domain variants substantially compromise kinase activity, suggesting that TNNI3K may influence human heart regenerative capacity and potentially also other aspects of human heart disease. We show that two kinase domain frameshift mutations in mice cause loss-of-function consequences by nonsense-mediated decay. We further show that the Tnni3k gene in two species of mole-rat has independently devolved into a pseudogene, presumably associated with the transition of these species to a low metabolism and hypoxic subterranean life. This may be explained by the observation that Tnni3k function in mice converges with oxidative stress to regulate mononuclear diploid cardiomyocyte frequency. Unlike other studied rodents, naked mole-rats have a surprisingly high (30%) mononuclear cardiomyocyte level but most of their mononuclear cardiomyocytes are polyploid; their mononuclear diploid cardiomyocyte level (7%) is within the known range (2–10%) of inbred mouse strains. Naked mole-rats provide further insight on a recent proposal that cardiomyocyte polyploidy is associated with evolutionary acquisition of endothermy. [ABSTRACT FROM AUTHOR]

Candida auris is an invasive and multidrug-resistant ascomycetous yeast that is under global surveillance. All clinical cases of C. auris infection diagnosed from 1997 to 2019 in Japan were non-invasive and sporadic otitis media cases. In the present study, we performed whole-genome sequencing of seven C. auris strains isolated from patients with otitis media in Japan, all of which belonged to clade II. Comparative genome analysis using the high-quality draft genome sequences JCM 15448T revealed that single nucleotide variations (SNVs), clade-specific accessory genes, and copy number variations (CNVs) were identified in each C. auris clade. A total of 61 genes involved in cell wall and stress response-related functions was absent in clade II, and the pattern of conserved CNVs in each clade was more stable in clade II than in other clades. Our data suggest that the genomic structural diversity is stable in C. auris isolated from each biogeographic location, and Japanese strains isolated from patients with otitis media might belong to an ancestral type of C. auris. One Japanese strain, TWCC 58362, with reduced susceptibility to fluconazole, exhibited no mutation in ergosterol biosynthesis-related genes (ERG). However, TWCC 58362-specific variations, including SNVs, indels, and CNVs were detected, suggesting that gene duplication events in C. auris might contribute to antifungal drug resistance. Taken together, we demonstrated that genomic structural variations in C. auris could correlate to geographical dissemination, epidemiology, lesions in the host, and antifungal resistance. [ABSTRACT FROM AUTHOR]

Background: Detection and pathology analysis of Mycobacterium leprae using skin biopsy tissues are essential for leprosy diagnosis and monitoring response to treatment. Although formalin fixation of patient tissues may not be ideal for molecular studies, biopsy samples are the most accessible material from suspected cases. Therefore, clinical molecular laboratories must be able to utilize formalin-fixed, paraffin-embedded (FFPE) material. Objective: To determine the best molecular method for diagnosing and monitoring leprosy in FFPE specimens, we developed a single-tube nested PCR (STNPCR) (131 bp) and SYBRGreen PCR (101 bp) assay using primers for the M. leprae-specific repetitive element (RLEP) gene and evaluated the results compared to those using previously established RLEP primers (372 bp). Methods: FFPE biopsy samples obtained from 145 leprosy patients (during or after multidrug therapy (MDT)) and patients with 29 other confounding dermatoses were examined by the bacteria index (BI) and by simple PCR, STNPCR, and SYBRGreen PCR using primers amplifying a 372-bp, 131-bp or 101-bp fragment of RLEP, respectively. Results: In leprosy patients receiving MDT, STNPCR showed a highest specificity of 100% and a positive predictive value (PPV) of 100%. For multibacillary (MB), paucibacillary (PB) and all leprosy patients, the highest sensitivities were 91.42%, 39.13%, and 67.92%, negative predictive values (NPVs) were 8.57%, 60.36%, and 32.07%, and the highest accuracies were 93.93%, 62.67%, and 74.81%, respectively, higher than the results of SYBRGreen PCR and simple PCR. For post-MDT leprosy patients, SYBRGreen PCR showed the highest sensitivity of 50.0%, highest specificity of 100%, a PPV of 100%, an NPV of 100% and the highest accuracy of 83.72% for MB patients, which were higher than those of STNPCR and simple PCR. STNPCR showed the highest sensitivity of 26.66% and 34.48%, highest specificity of 100% and 100%, a PPV of 100% and 100%, NPV of 72.50% and 60.21%, and highest accuracy of 75.00% and 67.24% for PB and leprosy patients, respectively, higher than those of SYBRGreen PCR and simple PCR. Conclusions: These findings suggest that STNPCR or SYBRGreen PCR (131-bp and 101-bp fragment amplification, respectively) for RLEP using FFPE specimens performs better as a diagnostic test and for monitoring response to MDT than does simple PCR based on 372-bp fragment amplification. Additionally, STNPCR showed increased sensitivity for PB diagnosis using FFPE specimens, which can be transferred remotely or retrieved from previous leprosy patients. [ABSTRACT FROM AUTHOR]

Background: Protease inhibitors (PI) are especially important in salvage therapy. Previous treatment failure with a PI containing regimen may elicit resistance mutations, reducing PI susceptibility and limiting treatment options. The aim of this study was to describe major PI mutations among patients exposed to at least one PI to evaluate predictors of mutation emergence and the impact of subtypes on resistance. Methodology: Partial HIV-1 pol sequences (Sanger Sequencing) from patients exposed to PI with virological failure were genotyped from January 2014 to December 2017. Drug resistance mutations (DRM), antiretroviral susceptibility (GSS) and subtypes, along clinical and laboratory parameters, were evaluated using logistic regression to access the predictors of mutation emergence. Results: In 27.5% (466/1696) of the cases at least one major PI mutations was identified, most commonly M46 (14.7%), V82 (13.8%) and I54 (13.3%). Mutations to NRTI and NNRTI were observed in 69.6% and 59.9%, respectively, of the 1696 sequences. Full activity to darunavir was predicted in 88% (1496/1696), but was only 57% among those with at least one PI-DRM. Subtype C sequences had less major PI-DRMs (10%, 9/87) compared to B (28%, 338/1216) or F (35%, 58/168) (p <0.001) but adjusted analysis suggested that this association is not independent from a shorter treatment time and fewer regimens (OR 0.59, Confidence Interval 95: 0.2–2.5, p = 0.48). Subtype F, together with NRTI mutations and longer time on treatment was associated to presence of PI-DRM, to a lower darunavir GSS and to mutations at codon I50. Conclusions: Among patients with PI-DRM, full activity to darunavir was compromised in almost half of the cases and efforts to detect failure at earlier time are warranted, particularly for HIV-1 subtype F that showed association to the emergence of resistance, with potential impact in protease inhibitors sequencing. Furthermore, NRTI mutations may serve as an indicative of sufficient adherence to allow PI-DRM emergence. [ABSTRACT FROM AUTHOR]

Background: Vector-borne pathogens are a significant public health concern worldwide. Infections with these pathogens, some of which are emerging, are likely under-recognized due to the lack of widely-available laboratory tests. There is an urgent need for further advancement in diagnostic modalities to detect new and known vector-borne pathogens. We evaluated the utility of metagenomic shotgun sequencing (MGS) as a pathogen agnostic approach for detecting vector-borne pathogens from human blood samples. Methods: Residual whole blood samples from patients with known infection with Babesia microti, Borrelia hermsii, Plasmodium falciparum, Mansonella perstans, Anaplasma phagocytophilum or Ehrlichia chaffeensis were studied. Samples underwent DNA extraction, removal of human DNA, whole genome amplification, and paired-end library preparation, followed by sequencing on Illumina HiSeq 2500. Bioinformatic analysis was performed using the Livermore Metagenomics Analysis Toolkit (LMAT), Metagenomic Phylogenetic Analysis (MetaPhlAn2), Genomic Origin Through Taxonomic CHAllenge (GOTTCHA) and Kraken 2. Results: Eight samples were included in the study (2 samples each for P. falciparum and A. phagocytophilum). An average of 27.5 million read pairs was generated per sample (range, 18.3–38.8 million) prior to removal of human reads. At least one of the analytic tools was able to detect four of six organisms at the genus level, and the organism present in five of eight specimens at the species level. Mansonella and Ehrlichia species were not detected by any of the tools; however, mitochondrial cytochrome c oxidase subunit I amino acid sequence analysis suggested the presence of M. perstans genetic material. Conclusions: MGS is a promising tool with the potential to evolve as a non-hypothesis driven diagnostic test to detect vector-borne pathogens, including protozoa and helminths. [ABSTRACT FROM AUTHOR]

Background: Prophages play a significant role in prokaryotic evolution, often altering the function of the cell that they infect via transfer of new genes e.g., virulence or antibiotic resistance factors, inactivation of existing genes or by modifying gene expression. Recently, phage therapy has gathered renewed interest as a promising alternative to control bacterial infections. Cataloging the repertoire of prophages in large collections of species’ genomes is an important initial step in understanding their evolution and potential therapeutic utility. However, current widely-used tools for identifying prophages within bacterial genome sequences are mainly web-based, can have long response times, and do not scale to keep pace with the many thousands of genomes currently being sequenced routinely. Methodology: In this work, we present ProphET, an easy to install prophage predictor to be used in Linux operation system, without the constraints associated with a web-based tool. ProphET predictions rely on similarity searches against a database of prophage genes, taking as input a bacterial genome sequence in FASTA format and its corresponding gene annotation in GFF. ProphET identifies prophages in three steps: similarity search, calculation of the density of prophage genes, and edge refinement. ProphET performance was evaluated and compared with other phage predictors based on a set of 54 bacterial genomes containing 267 manually annotated prophages. Findings and conclusions: ProphET identifies prophages in bacterial genomes with high precision and offers a fast, highly scalable alternative to widely-used web-based applications for prophage detection. [ABSTRACT FROM AUTHOR]

As a leading cause of neonatal sepsis, Streptococcus agalactiae, commonly known as Group B Streptococcus, is a major neonatal pathogen. Current global screening practices employ risk- or culture-based protocols for detection of these organisms. In Western Australia (WA), universal culture-based screening is provided, with subsequent intrapartum antibiotic prophylaxis for all S. agalactiae-positive women during labour. Widespread antibiotic exposure is not ideal and this is one of the factors driving development of vaccines against S. agalactiae. Vaccine candidates have focused on the capsule, surface proteins and pilus types, however, capsule serotypes are known to vary geographically. The aim of this study was to use genome sequencing to gain an understanding of the circulating genotypes in WA, and to assess variations in the associated gene pools. We sequenced 141 antenatal carriage (vaginal/rectal) isolates and 10 neonatal invasive disease isolates from WA. Based on the global PubMLST database, the 151 strains were characterised into 30 sequence types, with clustering of these mainly into clonal complexes 1, 12, 17, 19 and 23. Of the genes encoding eleven surface proteins that were analysed, the most prevalent were fbp, lmb and scpB which were present in ≥ 98% of isolates. A cluster of non-haemolytic isolates, one of which was a neonatal invasive disease isolate, appeared to lack the entire cyl locus. Admixture analysis of population structure revealed evidence of genetic transfer among the WA isolates across structural groups. When compared against the PubMLST S. agalactiae data, WA isolates showed high levels of strain diversity with minimal apparent clustering. This is the first whole genome sequence study of WA S. agalactiae isolates and also represents the first addition of Australian isolate data to PubMLST. This report provides insight into the distribution and diversity of vaccine targets of S. agalactiae within Western Australia, indicating that the most appropriate capsular vaccine for this population would be the proposed pentavalent (Cps Ia, Ib, II, III and V) preparation, whilst vaccines targeting surface proteins should ideally utilise Fbp, Lmb and/or ScpB. [ABSTRACT FROM AUTHOR]

Introduction: The prevalence of bacteremia caused by Gram negative non-fermentative (GNNF) bacteria has been increasing globally over the past decade. Many studies have investigated their epidemiology but focus on the common GNNF including Pseudomonas aeruginosa and Acinetobacter baumannii. Knowledge of the uncommon GNNF bacteremias is very limited. This study explores invasive bloodstream infection GNNF isolates that were initially unidentified after testing with standard microbiological techniques. All isolations were made during laboratory-based surveillance activities in two rural provinces of Thailand between 2006 and 2014. Methods: A subset of GNNF clinical isolates (204/947), not identified by standard manual biochemical methodologies were run on the BD Phoenix automated identification and susceptibility testing system. If an organism was not identified (12/204) DNA was extracted for whole genome sequencing (WGS) on a MiSeq platform and data analysis performed using 3 web-based platforms: Taxonomer, CGE KmerFinder and One Codex. Results: The BD Phoenix automated identification system recognized 92% (187/204) of the GNNF isolates, and because of their taxonomic complexity and high phenotypic similarity 37% (69/187) were only identified to the genus level. Five isolates grew too slowly for identification. Antimicrobial sensitivity (AST) data was not obtained for 93/187 (50%) identified isolates either because of their slow growth or their taxa were not in the AST database associated with the instrument. WGS identified the 12 remaining unknowns, four to genus level only. Conclusion: The GNNF bacteria are of increasing concern in the clinical setting, and our inability to identify these organisms and determine their AST profiles will impede treatment. Databases for automated identification systems and sequencing annotation need to be improved so that opportunistic organisms are better covered. [ABSTRACT FROM AUTHOR]

Cancer driver genes, i.e., oncogenes and tumor suppressor genes, are involved in the acquisition of important functions in tumors, providing a selective growth advantage, allowing uncontrolled proliferation and avoiding apoptosis. It is therefore important to identify these driver genes, both for the fundamental understanding of cancer and to help finding new therapeutic targets or biomarkers. Although the most frequently mutated driver genes have been identified, it is believed that many more remain to be discovered, particularly for driver genes specific to some cancer types. In this paper, we propose a new computational method called LOTUS to predict new driver genes. LOTUS is a machine-learning based approach which allows to integrate various types of data in a versatile manner, including information about gene mutations and protein-protein interactions. In addition, LOTUS can predict cancer driver genes in a pan-cancer setting as well as for specific cancer types, using a multitask learning strategy to share information across cancer types. We empirically show that LOTUS outperforms five other state-of-the-art driver gene prediction methods, both in terms of intrinsic consistency and prediction accuracy, and provide predictions of new cancer genes across many cancer types. [ABSTRACT FROM AUTHOR]

The gut microbial community structure of adult Thrips tabaci collected from 10 different agro-climatically diverse locations of India was characterized by using the Illumina MiSeq platform to amplify the V3 region of the 16S rRNA gene of bacteria present in the sampled insects. Analyses were performed to study the bacterial communities associated with Thrips tabaci in India. The complete bacterial metagenome of T. tabaci was comprised of 1662 OTUs of which 62.25% belong to known and 37.7% of unidentified/unknown bacteria. These OTUs constituted 21 bacterial phyla of 276 identified genera. Phylum Proteobacteria was predominant, followed by Actinobacteria, Firmicutes, Bacteroidetes and Cyanobacteria. Additionally, the occurrence of the reproductive endosymbiont, Wolbachia was detected at two locations (0.56%) of the total known OTUs. There is high variation in diversity and species richness among the different locations. Alpha-diversity metrics indicated the higher gut bacterial diversity at Bangalore and lowest at Rahuri whereas higher bacterial species richness at T. tabaci samples from Imphal and lowest at Jhalawar. Beta diversity analyses comparing bacterial communities between the samples showed distinct differences in bacterial community composition of T. tabaci samples from different locations. This paper also constitutes the first record of detailed bacterial communities associated with T. tabaci. The location-wise variation in microbial metagenome profile of T. tabaci suggests that bacterial diversity might be governed by its population genetic structure, environment and habitat. [ABSTRACT FROM AUTHOR]

Clostridium difficile (Cd) infection (CDI) typically occurs after antibiotic usage perturbs the gut microbiota. Mucosa-associated invariant T cells (MAIT) are found in the gut and their development is dependent on Major histocompatibility complex-related protein 1 (MR1) and the host microbiome. Here we were interested in determining whether the absence of MR1 impacts resistance to CDI. To this end, wild-type (WT) and MR1-/- mice were treated with antibiotics and then infected with Cd spores. Surprisingly, MR1-/- mice exhibited resistance to Cd colonization. 16S rRNA gene sequencing of feces revealed inherent differences in microbial composition. This colonization resistance was transferred from MR1-/- to WT mice via fecal microbiota transplantation, suggesting that MR1-dependent factors influence the microbiota, leading to CDI susceptibility. [ABSTRACT FROM AUTHOR]

Around the world, pansies are one of the most popular garden flowers, but they are generally sensitive to high temperatures, and this limits the practicality of planting them during the warmest days of the year. However, a few pansy germplasms with improved heat tolerance have been discovered or bred, but the mechanisms of their heat resistance are not understood. In this study, we investigated the transcript profiles of a heat-tolerant pansy inbred line, DFM16, in response to high temperatures using RNAseq. Approximately 55.48 Gb of nucleotide data were obtained and assembled into 167,576 unigenes with an average length of 959 bp, of which, 5,708 genes were found to be differentially expressed after heat treatments. Real-time qPCR was performed to validate the expression profiles of the selected genes. Nine metabolic pathways were found to be significantly enriched, in the analysis of the differentially expressed genes. Several potentially interesting genes that encoded putative transcription regulators or key components involving heat shock protein (HSP), heat shock transcription factors (HSF), and antioxidants biosynthesis, were identified. These genes were highlighted to indicate their significance in response to heat stress and will be used as candidate genes to improve pansy heat-tolerance in the future. [ABSTRACT FROM AUTHOR]

Dioecy (distinct male and female individuals) and scarce to non-flowering are common features of cultivated yam (Dioscorea spp.). However, the molecular mechanisms underlying flowering and sex determination in Dioscorea are largely unknown. We conducted SuperSAGE transcriptome profiling of male, female and monoecious individuals to identify flowering and sex-related genes in white Guinea yam (D. rotundata), generating 20,236 unique tags. Of these, 13,901 were represented by a minimum of 10 tags. A total 88 tags were significantly differentially expressed in male, female and monoecious plants, of which 18 corresponded to genes previously implicated in flower development and sex determination in multiple plant species. We validated the SuperSAGE data with quantitative real-time PCR (qRT-PCR)-based analysis of the expression of three candidate genes. We further investigated the flowering patterns of 1938 D. rotundata accessions representing diverse geographical origins over two consecutive years. Over 85% of accessions were either male or non-flowering, less than 15% were female, while monoecious plants were rare. Intensity of flowering varied between male and female plants, with the former flowering more abundantly than the latter. Candidate genes identified in this study can be targeted for further validation and to induce regular flowering in poor to non-flowering cultivars. Findings of the study provide important inputs for further studies aiming to overcome the challenge of flowering in yams and to improve efficiency of yam breeding. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance (AMR) is currently one of the most important challenges to the treatment of bacterial infections. A critical issue to combat AMR is to restrict its spread. In several instances, bacterial plasmids are involved in the global spread of AMR. Plasmids belonging to the incompatibility group (Inc)HI are widespread in Enterobacteriaceae and most of them express multiple antibiotic resistance determinants. They play a relevant role in the recent spread of colistin resistance. We present in this report novel findings regarding IncHI plasmid conjugation. Conjugative transfer in liquid medium of an IncHI plasmid requires expression of a plasmid-encoded, large-molecular-mass protein that contains an Ig-like domain. The protein, termed RSP, is encoded by a gene (ORF R0009) that maps in the Tra2 region of the IncHI1 R27 plasmid. The RSP protein is exported outside the cell by using the plasmid-encoded type IV secretion system that is also used for its transmission to new cells. Expression of the protein reduces cell motility and enables plasmid conjugation. Flagella are one of the cellular targets of the RSP protein. The RSP protein is required for a high rate of plasmid transfer in both flagellated and nonflagellated Salmonella cells. This effect suggests that RSP interacts with other cellular structures as well as with flagella. These unidentified interactions must facilitate mating pair formation and, hence, facilitate IncHI plasmid conjugation. Due to its location on the outer surfaces of the bacterial cell, targeting the RSP protein could be a means of controlling IncHI plasmid conjugation in natural environments or of combatting infections caused by AMR enterobacteria that harbor IncHI plasmids. [ABSTRACT FROM AUTHOR]

High-throughput multi-omics studies and corresponding network analyses of multi-omic data have rapidly expanded their impact over the last 10 years. As biological features of different types (e.g. transcripts, proteins, metabolites) interact within cellular systems, the greatest amount of knowledge can be gained from networks that incorporate multiple types of -omic data. However, biological and technical sources of variation diminish the ability to detect cross-type associations, yielding networks dominated by communities comprised of nodes of the same type. We describe here network building methods that can maximize edges between nodes of different data types leading to integrated networks, networks that have a large number of edges that link nodes of different–omic types (transcripts, proteins, lipids etc). We systematically rank several network inference methods and demonstrate that, in many cases, using a random forest method, GENIE3, produces the most integrated networks. This increase in integration does not come at the cost of accuracy as GENIE3 produces networks of approximately the same quality as the other network inference methods tested here. Using GENIE3, we also infer networks representing antibody-mediated Dengue virus cell invasion and receptor-mediated Dengue virus invasion. A number of functional pathways showed centrality differences between the two networks including genes responding to both GM-CSF and IL-4, which had a higher centrality value in an antibody-mediated vs. receptor-mediated Dengue network. Because a biological system involves the interplay of many different types of molecules, incorporating multiple data types into networks will improve their use as models of biological systems. The methods explored here are some of the first to specifically highlight and address the challenges associated with how such multi-omic networks can be assembled and how the greatest number of interactions can be inferred from different data types. The resulting networks can lead to the discovery of new host response patterns and interactions during viral infection, generate new hypotheses of pathogenic mechanisms and confirm mechanisms of disease. [ABSTRACT FROM AUTHOR]

Glioblastoma multiforme (GBM) is the most aggressive type of brain tumor. Molecular heterogeneity is a hallmark of GBM tumors that is a barrier in developing treatment strategies. In this study, we used the nonsynonymous mutations of GBM tumors deposited in The Cancer Genome Atlas (TCGA) and applied a systems level approach based on biophysical characteristics of mutations and their organization in patient-specific subnetworks to reduce inter-patient heterogeneity and to gain potential clinically relevant insights. Approximately 10% of the mutations are located in “patches” which are defined as the set of residues spatially in close proximity that are mutated across multiple patients. Grouping mutations as 3D patches reduces the heterogeneity across patients. There are multiple patches that are relatively small in oncogenes, whereas there are a small number of very large patches in tumor suppressors. Additionally, different patches in the same protein are often located at different domains that can mediate different functions. We stratified the patients into five groups based on their potentially affected pathways, revealed from the patient-specific subnetworks. These subnetworks were constructed by integrating mutation profiles of the patients with the interactome data. Network-guided clustering showed significant association between each group and patient survival (P-value = 0.0408). Also, each group carries a set of signature 3D mutation patches that affect predominant pathways. We integrated drug sensitivity data of GBM cell lines with the mutation patches and the patient groups to analyze the therapeutic outcome of these patches. We found that Pazopanib might be effective in Group 3 by targeting CSF1R. Additionally, inhibiting ATM that is a mediator of PTEN phosphorylation may be ineffective in Group 2. We believe that from mutations to networks and eventually to clinical and therapeutic data, this study provides a novel perspective in the network-guided precision medicine. [ABSTRACT FROM AUTHOR]

The human gut microbiota is well established as an important factor in health and disease. Fecal sample microbiota are often analyzed as a proxy for gut microbiota, and characterized with respect to their composition profiles. Modern approaches employ whole genome shotgun next-generation sequencing as the basis for these analyses. Sequencing depth as well as choice of next-generation sequencing data analysis method constitute two main interacting methodological factors for such an approach. In this study, we used 200 million sequence read pairs from one fecal sample for comparing different taxonomy classification methods, using default and custom-made reference databases, at different sequencing depths. A mock community data set with known composition was used for validating the classification methods. Results suggest that sequencing beyond 60 million read pairs does not seem to improve classification. The phylogeny prediction pattern, when using the default databases and the consensus database, appeared to be similar for all three methods. Moreover, these methods predicted rather different species. We conclude that the choice of sequencing depth and classification method has important implications for taxonomy composition prediction. A multi-method-consensus approach for robust gut microbiota NGS analysis is recommended. [ABSTRACT FROM AUTHOR]

Background: Exacerbations of chronic obstructive pulmonary disease (COPD) are debilitating events and spur disease progression. Infectious causes are frequent; however, it is unknown to what extent exacerbations are caused by larger shifts in the airways’ microbiota. The aim of the current study was to analyse the changes in microbial composition between stable state and during exacerbations, and the corresponding immune response. Methods: The study sample included 36 COPD patients examined at stable state and exacerbation from the Bergen COPD Cohort and Exacerbations studies, and one patient who delivered sputum on 13 different occasions during the three-year study period. A physician examined the patients at all time points, and sputum induction was performed by stringent protocol. Only induced sputum samples were used in the current study, not spontaneously expectorated sputum. Sputum inflammatory markers (IL-6, IL-8, IL-18, IP-10, MIG, TNF-α) and antimicrobial peptides (AMPs, i.e. LL-37/hCAP-18, SLPI) were measured in supernatants, whereas target gene sequencing (16S rRNA) was performed on corresponding cell pellets. The microbiome bioinformatics platform QIIME2TM and the statistics environment R were applied for bioinformatics analyses. Results: Levels of IP-10, MIG, TNF-α and AMPs were significantly different between the two disease states. Of 36 sample pairs, 24 had significant differences in the 12 most abundant genera between disease states. The diversity was significantly different in several individuals, but not when data was analysed on a group level. The one patient case study showed longitudinal dynamics in microbiota unrelated to disease state. Conclusion: Changes in the sputum microbiota with changing COPD disease states are common, and are accompanied by changes in inflammatory markers. However, the changes are highly individual and heterogeneous events. [ABSTRACT FROM AUTHOR]

Interception of potential invasive species at ports-of-entry is essential for effective biosecurity and biosurveillance programs. However, taxonomic assessment of the immature stages of most arthropods is challenging; characters for identification are often dependent on adult morphology and reproductive structures. This study aims to strengthen the identification of such specimens through DNA barcoding, with a focus on microlepidoptera. A sample of 241 primarily immature microlepidoptera specimens intercepted at U.S. ports-of-entry from 2007 to 2011 were selected for analysis. From this sample, 201 COI-5P sequences were generated and analyzed for concordance between morphology-based and DNA-based identifications. The retrospective analysis of the data over 10 years (2009 to 2019) using the Barcode of Life Data (BOLD) system demonstrates the importance of establishing and growing DNA barcode reference libraries for use in specimen identification. Additionally, analysis of specimen identification using public data (43.3% specimens identified) vs. non-public data (78.6% specimens identified) highlights the need to encourage researchers to make data publicly accessible. DNA barcoding surpassed morphological identification with 42.3% (public) and 66.7% (non-public) of the sampled specimens achieving a species-level identification, compared to 38.3% species-level identification by morphology. Whilst DNA barcoding was not able to identify all specimens in our dataset, its incorporation into border security programs as an adjunct to morphological identification can provide secondary lines of evidence and lower taxonomic resolution in many cases. Furthermore, with increased globalization, database records need to be clearly annotated for suspected specimen origin versus interception location. [ABSTRACT FROM AUTHOR]

Mixed community or environmental DNA marker gene sequencing has become a commonly used technique for biodiversity analyses in freshwater systems. Many cytochrome c oxidase subunit I (COI) primer sets are now available for such work. The purpose of this study is to test whether COI primer choice affects the recovery of arthropod richness, beta diversity, and recovery of target assemblages in the benthos kick-net samples typically used in freshwater biomonitoring. We examine six commonly used COI primer sets on samples collected from six freshwater sites. Biodiversity analyses show that richness is sensitive to primer choice and the combined use of multiple COI amplicons recovers higher richness. Thus, to recover maximum richness, multiple primer sets should be used with COI metabarcoding. In ordination analyses based on community dissimilarity, samples consistently cluster by site regardless of amplicon choice or PCR replicate. Thus, for broadscale community analyses, overall beta diversity patterns are robust to COI marker choice. Recovery of traditional freshwater bioindicator assemblages such as Ephemeroptera, Trichoptera, Plectoptera, and Chironomidae as well as Arthropoda site indicators were differentially detected by each amplicon tested. This work will help future biodiversity and biomonitoring studies develop not just standardized, but optimized workflows that either maximize taxon-detection or the selection of amplicons for water quality or Arthropoda site indicators. [ABSTRACT FROM AUTHOR]

Background: Although gross vascular invasion (VI) has prognostic significance in patients with hepatocellular carcinoma (HCC) who have undergone hepatic resection, few studies have investigated the relationship between gross VI and aberrant expression of microribonucleic acids (miRNAs and miRs). Thus, the objective of this study was to identify miRNAs selectively expressed in HCC with gross VI and investigate their prognostic significance. Materials and methods: Eligible two datasets (accession number: GSE20594 and GSE67140) were collected from the National Center for Biotechnology Information’s (NCBI) Gene Expression Omnibus (GEO) database to compare miRNAs expression between HCC with and without gross VI. Differentially expressed miRNAs were externally validated using expression data from The Cancer Genome Atlas (TCGA) database. Prognostic significance and predicted functions of selected miRNAs for HCC were also investigated. Results: Thirty-five miRNAs were differentially expressed between HCC with and without gross VI in both datasets. Among them, three miRNAs were validated using TCGA database. miR-99a, miR-100, and miR-148a were downregulated to a greater extent in patients with HCC and gross VI than in those with HCC but no gross VI. Receiver operating characteristic (ROC) curve analysis showed discriminatory power of these miRNAs in predicting gross VI. Multivariate survival analysis revealed that types of surgery, advanced tumor node metastasis (TNM) stage, and low expression of miR-100-5p were independently associated with tumor recurrence. It also revealed that types of surgery, advanced TNM stage, low expression of miR-100-5p and miR-148a-3p were independent risk factors for overall survival (OS) after hepatic resection for HCC. A text mining analysis revealed that these miRNAs were linked to multifaceted hallmarks of cancer, including “invasion and metastasis.” Conclusions: Low expressions of miR-100-5p and miR-148a-3p were associated with gross VI and poor survival of patients after hepatic resection for HCC. [ABSTRACT FROM AUTHOR]

Background: As a result of decades of effort by many investigators we now have an advanced level of understanding about several molecular systems involved in the control of gene expression. Examples include CpG islands, promoters, mRNA splicing and epigenetic signals. It is less clear, however, how such systems work together to integrate the functions of a living organism. Here I describe the results of a study to test the idea that a contribution might be made by focusing on genes specifically expressed in a particular tissue, the human testis. Experimental design: A database of 239 testis-specific genes was accumulated and each was examined for the presence of features relevant to control of gene expression. These include: (1) the presence of a promoter, (2) the presence of a CpG island (CGI) within the promoter, (3) the presence in the promoter of a transcription factor binding site near the transcription start site, (4) the level of gene expression, and (5) the above features in genes of testis-specific cell types such as spermatocyte and spermatid that differ in their extent of differentiation. Results: Of the 107 database genes with an annotated promoter, 56 were found to have one or more transcription factor binding sites near the transcription start site. Three of the binding sites observed, Pax-5, AP-2αA and GRα, stand out in abundance suggesting they may be involved in testis-specific gene expression. Compared to less differentiated testis-specific cells, genes of more differentiated cells were found to be (1) more likely to lack a CGI, (2) more likely to lack introns and (3) higher in expression level. The results suggest genes of more differentiated cells have a reduced need for CGI-based regulatory repression, reduced usage of gene splicing and a smaller set of expressed proteins. [ABSTRACT FROM AUTHOR]

Background: More than 11,000 laboratories and companies developed their own next-generation sequencing (NGS) for screening and diagnosis of various diseases including cancer. Although inconsistencies of mutation calls as high as 43% in databases such as GDSC (Genomics of Drug Sensitivity in Cancer) and CCLE (Cancer Cell Line Encyclopedia) have been reported, not many studies on the reasons for the inconsistencies have been published. Methods: Targeted-NGS analysis of 151 genes in 35 cell lines common to GDSC and CCLE was performed, and the results were compared with those from GDSC and CCLE wherein whole-exome- or highly-multiplex NGS were employed. Results: In the comparison, GDSC and CCLE had a high rate (40–45%) of false-negative (FN) errors which would lead to high rate of inconsistent mutation calls, suggesting that highly-multiplex NGS may have high rate of FN errors. We also posited the possibility that targeted NGS, especially for the detection of low-level cancer cells in cancer tissues might suffer significant FN errors. Conclusion: FN errors may be the most important errors in NGS testing for cancer; their evaluation in laboratory-developed NGS tests is needed. [ABSTRACT FROM AUTHOR]

Methylation patterns established and maintained at CpG sites may be altered by single nucleotide polymorphisms (SNPs) within these sites and may affect the regulation of nearby genes. Our aims were to: 1) identify and generate a database of SNPs potentially subject to epigenetic control by DNA methylation via their involvement in creating, removing or displacing CpG sites (meSNPs), and; 2) investigate the association of these meSNPs with CpG islands (CGIs), and with methylation profiles of DNA extracted from tissues from cattle with divergent feed efficiencies detected using MIRA-Seq. Using the variant annotation for 56,969,697 SNPs identified in Run5 of the 1000 Bull Genomes Project and the UMD3.1.1 bovine reference genome sequence assembly, we identified and classified 12,836,763 meSNPs according to the nature of variation created at CpGs. The majority of the meSNPs were located in intergenic regions (68%) or introns (26.3%). We found an enrichment (p<0.01) of meSNPs located in CGIs relative to the genome as a whole, and also in differentially methylated sequences in tissues from animals divergent for feed efficiency. Seven meSNPs, located in differentially methylated regions, were fixed for methylation site creating (MSC) or destroying (MSD) alleles in the differentially methylated genomic sequences of animals differing in feed efficiency. These meSNPs may be mechanistically responsible for creating or deleting methylation targets responsible for the differential expression of genes underlying differences in feed efficiency. Our methyl SNP database (dbmeSNP) is useful for identifying potentially functional "epigenetic polymorphisms" underlying variation in bovine phenotypes. [ABSTRACT FROM AUTHOR]

A comprehensive knowledge of the types and ratios of microbes that inhabit the healthy human gut is necessary before any kind of pre-clinical or clinical study can be performed that attempts to alter the microbiome to treat a condition or improve therapy outcome. To address this need we present an innovative scalable comprehensive analysis workflow, a healthy human reference microbiome list and abundance profile (GutFeelingKB), and a novel Fecal Biome Population Report (FecalBiome) with clinical applicability. GutFeelingKB provides a list of 157 organisms (8 phyla, 18 classes, 23 orders, 38 families, 59 genera and 109 species) that forms the baseline biome and therefore can be used as healthy controls for studies related to dysbiosis. This list can be expanded to 863 organisms if closely related proteomes are considered. The incorporation of microbiome science into routine clinical practice necessitates a standard report for comparison of an individual’s microbiome to the growing knowledgebase of “normal” microbiome data. The FecalBiome and the underlying technology of GutFeelingKB address this need. The knowledgebase can be useful to regulatory agencies for the assessment of fecal transplant and other microbiome products, as it contains a list of organisms from healthy individuals. In addition to the list of organisms and their abundances, this study also generated a collection of assembled contiguous sequences (contigs) of metagenomics dark matter. In this study, metagenomic dark matter represents sequences that cannot be mapped to any known sequence but can be assembled into contigs of 10,000 nucleotides or higher. These sequences can be used to create primers to study potential novel organisms. All data is freely available from and NCBI’s Short Read Archive. [ABSTRACT FROM AUTHOR]

Despite the importance of microbial activity in mobilizing arsenic in groundwater aquifers, the phylogenetic distribution of contributing microbial metabolisms is understudied. Groundwater samples from Ohio aquifers were analyzed using metagenomic sequencing to identify functional potential that could drive arsenic cycling, and revealed mechanisms for direct (i.e., Ars system) and indirect (i.e., iron reduction) arsenic mobilization in all samples, despite differing geochemical conditions. Analyses of 194 metagenome-assembled genomes (MAGs) revealed widespread functionality related to arsenic mobilization throughout the bacterial tree of life. While arsB and arsC genes (components of an arsenic resistance system) were found in diverse lineages with no apparent phylogenetic bias, putative aioA genes (aerobic arsenite oxidase) were predominantly identified in Methylocystaceae MAGs. Both previously described and undescribed respiratory arsenate reduction potential via arrA was detected in Betaproteobacteria, Deltaproteobacteria, and Nitrospirae MAGs, whereas sulfate reduction potential was primarily limited to members of the Deltaproteobacteria and Nitrospirae. Lastly, iron reduction potential was detected in the Ignavibacteria, Deltaproteobacteria, and Nitrospirae. These results expand the phylogenetic distribution of taxa that may play roles in arsenic mobilization in subsurface systems. Specifically, the Nitrospirae are a much more functionally diverse group than previously assumed and may play key biogeochemical roles in arsenic-contaminated ecosystems. [ABSTRACT FROM AUTHOR]

Chromatin immunoprecipitation followed by sequencing, i.e. ChIP-Seq, is a widely used experimental technology for the identification of functional protein-DNA interactions. Nowadays, such databases as ENCODE, GTRD, ChIP-Atlas and ReMap systematically collect and annotate a large number of ChIP-Seq datasets. Comprehensive control of dataset quality is currently indispensable to select the most reliable data for further analysis. In addition to existing quality control metrics, we have developed two novel metrics that allow to control false positives and false negatives in ChIP-Seq datasets. For this purpose, we have adapted well-known population size estimate for determination of unknown number of genuine transcription factor binding regions. Determination of the proposed metrics was based on overlapping distinct binding sites derived from processing one ChIP-Seq experiment by different peak callers. Moreover, the metrics also can be useful for assessing quality of datasets obtained from processing distinct ChIP-Seq experiments by a given peak caller. We also have shown that these metrics appear to be useful not only for dataset selection but also for comparison of peak callers and identification of site motifs based on ChIP-Seq datasets. The developed algorithm for determination of the false positive control metric and false negative control metric for ChIP-Seq datasets was implemented as a plugin for a BioUML platform: . [ABSTRACT FROM AUTHOR]

Background: Genomic data have become major resources to understand complex mechanisms at fine-scale temporal and spatial resolution in functional and evolutionary genetic studies, including human diseases, such as cancers. Recently, a large number of whole genomes of evolving populations of yeast (Saccharomyces cerevisiae W303 strain) were sequenced in a time-dependent manner to identify temporal evolutionary patterns. For this type of study, a chromosome-level sequence assembly of the strain or population at time zero is required to compare with the genomes derived later. However, there is no fully automated computational approach in experimental evolution studies to establish the chromosome-level genome assembly using unique features of sequencing data. Methods and results: In this study, we developed a new software pipeline, the integrative meta-assembly pipeline (IMAP), to build chromosome-level genome sequence assemblies by generating and combining multiple initial assemblies using three de novo assemblers from short-read sequencing data. We significantly improved the continuity and accuracy of the genome assembly using a large collection of sequencing data and hybrid assembly approaches. We validated our pipeline by generating chromosome-level assemblies of yeast strains W303 and SK1, and compared our results with assemblies built using long-read sequencing and various assembly evaluation metrics. We also constructed chromosome-level sequence assemblies of S. cerevisiae strain Sigma1278b, and three commonly used fungal strains: Aspergillus nidulans A713, Neurospora crassa 73, and Thielavia terrestris CBS 492.74, for which long-read sequencing data are not yet available. Finally, we examined the effect of IMAP parameters, such as reference and resolution, on the quality of the final assembly of the yeast strains W303 and SK1. Conclusions: We developed a cost-effective pipeline to generate chromosome-level sequence assemblies using only short-read sequencing data. Our pipeline combines the strengths of reference-guided and meta-assembly approaches. Our pipeline is available online at including a Docker image, as well as a Perl script, to help users install the IMAP package, including several prerequisite programs. Users can use IMAP to easily build the chromosome-level assembly for the genome of their interest. [ABSTRACT FROM AUTHOR]

Changing environmental conditions, including those caused by human activities, reshape biological communities through both loss of native species and establishment of non-native species in the altered habitats. Dynamic interactions with the abiotic environment impact both immigration and initial establishment of non-native species into these altered habitats. The repeated emergence of disease systems in urban areas worldwide highlights the importance of understanding how dynamic migratory processes affect the current and future distribution and abundance of pathogens in urban environments. In this study, we examine the pattern of invasion of Trypanosoma cruzi—the causative agent of human Chagas disease—in the city of Arequipa, Peru. Phylogenetic analyses of 136 T. cruzi isolates from Arequipa and other South American locations suggest that only one T. cruzi lineage established a population in Arequipa as all T. cruzi isolated from vectors in Arequipa form a recent monophyletic group within the broader South American phylogeny. We discuss several hypotheses that may explain the limited number of established T. cruzi lineages despite multiple introductions of the parasite. [ABSTRACT FROM AUTHOR]

Fine-mapping of regions linked to the inheritance of hypertension is accomplished by genetic dissection of blood pressure quantitative trait loci (BP QTLs) in rats. The goal of the current study was to further fine-map two genomic regions on rat chromosome 1 with opposing blood pressure effects (BP QTL1b1 and BP QTL1b1a), the homologous region of which on human chromosome 15 harbors BP QTLs. Two new substrains were constructed and studied from the previously reported BP QTL1b1, one having significantly lower systolic BP by 17 mmHg than that of the salt-sensitive (S) rat (P = 0.007). The new limits of BP QTL1b1 were between 134.09 Mb and 135.40 Mb with a 43% improvement from the previous 2.31 Mb to the current 1.31 Mb interval containing 4 protein-coding genes (Rgma, Chd2, Fam174b, and St8sia2), 2 predicted miRNAs, and 4 lncRNAs. One new substrain was constructed and studied from the previously reported BPQTL1b1a having a significantly higher systolic BP by 22 mmHg (P = 0.006) than that of the S rat. The new limits of BPQTL1b1a were between 133.53 Mb and 134.52 Mb with a 32% improvement from the previous1.45 Mb to the current 990.21 Kb interval containing 1 protein-coding gene, Mctp2, and a lncRNA. The congenic segments of these two BP QTLs overlapped between 134.09 Mb and 134.52 Mb. No exonic variants were detected in any of the genes. These findings reiterate complexity of genetic regulation of BP within QTL regions, where elements beyond protein-coding sequences could be factors in controlling BP. [ABSTRACT FROM AUTHOR]

Gene set analysis (GSA) has become the common methodology for analyzing transcriptomics data. However, self-contained GSA techniques are rarely, if ever, used for proteomics data analysis. Here we present a self-contained proteome level GSA of four consensus molecular subtypes (CMSs) previously established by transcriptome dissection of colon carcinoma specimens. Despite notable difference in structure of proteomics and transcriptomics data, many pathway-wide characteristic features of CMSs found at the mRNA level were reproduced at the protein level. In particular, CMS1 features show heavy involvement of immune system as well as the pathways related to mismatch repair, DNA replication and functioning of proteasome, while CMS4 tumors upregulate complement pathway and proteins participating in epithelial-to-mesenchymal transition (EMT). In addition, protein level GSA yielded a set of novel observations visible at the proteome, but not at the transcriptome level, including possible involvement of major histocompatibility complex II (MHC-II) antigens in the known immunogenicity of CMS1 and a connection between cholesterol trafficking and the regulation of Integrin-linked kinase (ILK) in CMS3. Overall, this study proves utility of self-contained GSA approaches as a critical tool for analyzing proteomics data in general and dissecting protein-level molecular portraits of human tumors in particular. [ABSTRACT FROM AUTHOR]

Extended soil contamination by polychlorinated biphenyls (PCBs) represents a global environmental issue that can hardly be addressed with the conventional remediation treatments. Rhizoremediation is a sustainable alternative, exploiting plants to stimulate in situ the degradative bacterial communities naturally occurring in historically polluted areas. This approach can be enhanced by the use of bacterial strains that combine PCB degradation potential with the ability to promote plant and root development. With this aim, we established a collection of aerobic bacteria isolated from the soil of the highly PCB-polluted site “SIN Brescia-Caffaro” (Italy) biostimulated by the plant Phalaris arundinacea. The strains, selected on biphenyl and plant secondary metabolites provided as unique carbon source, were largely dominated by Actinobacteria and a significant number showed traits of interest for remediation, harbouring genes homologous to bphA, involved in the PCB oxidation pathway, and displaying 2,3-catechol dioxygenase activity and emulsification properties. Several strains also showed the potential to alleviate plant stress through 1-aminocyclopropane-1-carboxylate deaminase activity. In particular, we identified three Rhodococcus strains able to degrade in vitro several PCB congeners and to promote lateral root emergence in the model plant Arabidopsis thaliana in vivo. In addition, these strains showed the capacity to colonize the root system and to increase the plant biomass in PCB contaminated soil, making them ideal candidates to sustain microbial-assisted PCB rhizoremediation through a bioaugmentation approach. [ABSTRACT FROM AUTHOR]

Strongyloidiasis is caused by the human infective nematodes Strongyloides stercoralis, Strongyloides fuelleborni subsp. fuelleborni and Strongyloides fuelleborni subsp. kellyi. The zoonotic potential of S. stercoralis and the potential role of dogs in the maintenance of strongyloidiasis transmission has been a topic of interest and discussion for many years. In Australia, strongyloidiasis is prevalent in remote socioeconomically disadvantaged communities in the north of the continent. Being an isolated continent that has been separated from other regions for a long geological period, description of diversity of Australian Strongyloides genotypes adds to our understanding of the genetic diversity within the genus. Using PCR and amplicon sequencing (Illumina sequencing technology), we sequenced the Strongyloides SSU rDNA hyper-variable I and hyper-variable IV regions using Strongyloides-specific primers, and a fragment of the mtDNA cox1 gene using primers that are broadly specific for Strongyloides sp. and hookworms. These loci were amplified from DNA extracted from Australian human and dog faeces, and one human sputum sample. Using this approach, we confirm for the first time that potentially zoonotic S. stercoralis populations are present in Australia, suggesting that dogs represent a potential reservoir of human strongyloidiasis in remote Australian communities. [ABSTRACT FROM AUTHOR]

Mast flowering is synchronised highly variable flowering by a population of perennial plants over a wide geographical area. High seeding years are seen as a threat to native and endangered species due to high predator density caused by the abundance of seed. An understanding of the molecular pathways that influence masting behaviour in plants could provide better prediction of a forthcoming masting season and enable conservation strategies to be deployed. The goal of this study was to identify candidate flowering genes that might be involved in regulating mast flowering. To achieve this, high-throughput large-scale RNA-sequencing was performed on two masting plant species, Celmisia lyallii (Asteraceae), and Chionochloa pallens (Poaceae) to develop a reference transcriptome for functional and molecular analysis. An average total of 33 million 150 base-paired reads, for both species, were assembled using the Trinity pipeline, resulting in 151,803 and 348,649 transcripts respectively for C. lyallii and C. pallens. For both species, about 56% of the unigenes were annotated with gene descriptions to known proteins followed by Gene Ontology analysis, categorising them on the basis of putative biological processes, molecular function, and cellular localization. A total of 543 transcripts from C. lyallii and 470 transcripts from C. pallens were also mapped to unique flowering-time proteins identified in Arabidopsis thaliana, suggesting the conservation of the flowering network in these wild alpine plants growing in natural field conditions. Expression analysis of several selected homologous flowering-pathway genes showed seasonal and photoperiodic variations. These genes can further be analysed to understand why seasonal cues, such as the increasing photoperiod in spring, that triggers the annual flowering of most plants, are insufficient to always trigger flowering in masting plants and to uncover the molecular basis of how additional cues (such as temperature during the previous growing seasons) then determines flowering in mast years. [ABSTRACT FROM AUTHOR]

Caretta caretta is the most common sea turtle species in the Mediterranean Sea. The species is threatened by anthropomorphic activity that causes thousands of deaths and hundreds of strandings along the Mediterranean coast. Stranded turtles are often cared for in rehabilitation centres until they recover or die. The objective of this study was to characterize the gut microbiome of nine sea turtles stranded along the Sicilian coast of the Mediterranean Sea using high-throughput sequencing analysis targeting V3–V4 regions of the bacterial 16S rRNA gene. Stool samples were collected from eight specimens hosted in the recovery centre after a few days of hospitalization (under 7) and from one hosted for many weeks (78 days). To better explore the role of bacterial communities in loggerhead sea turtles, we compared our data with published fecal microbiomes from specimens stranded along the Tuscan and Ligurian coast. Our results highlight that, despite the different origin, size and health conditions of the animals, Firmicutes, Bacteroidetes and Proteobacteria constitute the main components of the microbiota. This study widens our knowledge on the gut microbiome of sea turtles and could be helpful for the set up of rehabilitation therapies of stranded animals after recovery in specialized centres. [ABSTRACT FROM AUTHOR]

Dengue fever is caused by dengue viruses (DENV) from the Flavivirus genus and is the most prevalent arboviral disease. DENV exists in four immunogenically distinct and genetically-related serotypes (DENV-1 to 4), each subdivided in genotypes. Despite the endemicity of all four DENV serotypes in Thailand, no prior study has characterized the circulation of DENV in the southern provinces of the country. To determine the genetic diversity of DENV circulating in Southern Thailand in 2015 and 2016, we investigated 46 viruses from 182 patients’ sera confirmed positive for DENV by serological and Nested RT-PCR tests. Our dataset included 2 DENV-1, 20 DENV-2, 9 DENV-3 and 15 DENV-4. Phylogenetic analysis was performed on viral envelop sequences. This revealed that part of the identified genotypes from DENV-1 and DENV-4 had been predominant in Asia (genotype I for both serotypes), while genotype II for DENV-4 and the Cosmopolitan genotype DENV-2 were also circulating. Whereas DENV-3 genotype II had been predominantly detected in South East Asia during the previous decades, we found genotype III and genotype I in Southern Thailand. All DENV genotype identified in this study were closely related to contemporary strains circulating in Southeast Asian countries, emphasizing the regional circulation of DENV. These results provide new insights into the co-circulation of all four DENV serotypes in Southern Thailand, confirming the hyperendemicity of DENV in the region. These findings also suggest a new trend of dissemination for some DENV serotypes with a possible shift in genotype distribution; as recently observed in other Asian countries. [ABSTRACT FROM AUTHOR]

Protein solubility is a critical prerequisite to any proteomics analysis. Combination of urea/thiourea and 3-[(3-cholamidopropyl)dimethylammonio]-1-propanesulfonate (CHAPS) have been routinely used to enhance protein solubilization for oil palm proteomics studies in recent years. The goals of these proteomics analysis are essentially to complement the knowledge regarding the regulation networks and mechanisms of the oil palm fatty acid biosynthesis. Through omics integration, the information is able to build a regulatory model to support efforts in improving the economic value and sustainability of palm oil in the global oil and vegetable market. Our study evaluated the utilization of sodium deoxycholate as an alternative solubilization buffer/additive to urea/thiourea and CHAPS. Efficiency of urea/thiourea/CHAPS, urea/CHAPS, urea/sodium deoxycholate and sodium deoxycholate buffers in solubilizing the oil palm (Elaeis guineensis var. Tenera) mesocarp proteins were compared. Based on the protein yields and electrophoretic profile, combination of urea/thiourea/CHAPS were shown to remain a better solubilization buffer and additive, but the differences with sodium deoxycholate buffer was insignificant. A deeper mass spectrometric and statistical analyses on the identified proteins and peptides from all the evaluated solubilization buffers revealed that sodium deoxycholate had increased the number of identified proteins from oil palm mesocarps, enriched their gene ontologies and reduced the number of carbamylated lysine residues by more than 67.0%, compared to urea/thiourea/CHAPS buffer. Although only 62.0% of the total identified proteins were shared between the urea/thiourea/CHAPS and sodium deoxycholate buffers, the importance of the remaining 38.0% proteins depends on the applications. The only observed limitations to the application of sodium deoxycholate in protein solubilization were the interference with protein quantitation and but it could be easily rectified through a 4-fold dilution. All the proteomics data are available via ProteomeXchange with identifier PXD013255. In conclusion, sodium deoxycholate is applicable in the solubilization of proteins extracted from oil palm mesocarps with higher efficiency compared to urea/thiourea/CHAPS buffer. The sodium deoxycholate buffer is more favorable for proteomics analysis due to its proven advantages over urea/thiourea/CHAPS buffer. [ABSTRACT FROM AUTHOR]

Essential tremor (ET) is one of the most common movement disorders. The etiology of ET remains largely unexplained. Whole genome sequencing (WGS) is likely to be of value in understanding a large proportion of ET with Mendelian and complex disease inheritance patterns. In ET families with Mendelian inheritance patterns, WGS may lead to gene identification where WES analysis failed to identify the causative single nucleotide variant (SNV) or indel due to incomplete coverage of the entire coding region of the genome, in addition to accurate detection of larger structural variants (SVs) and copy number variants (CNVs). Alternatively, in ET families with complex disease inheritance patterns with gene x gene and gene x environment interactions enrichment of functional rare coding and non-coding variants may explain the heritability of ET. We performed WGS in eight ET families (n = 40 individuals) enrolled in the Family Study of Essential Tremor. The analysis included filtering WGS data based on allele frequency in population databases, rare SNV and indel classification and association testing using the Mixed-Model Kernel Based Adaptive Cluster (MM-KBAC) test. A separate analysis of rare SV and CNVs segregating within ET families was also performed. Prioritization of candidate genes identified within families was performed using phenolyzer. WGS analysis identified candidate genes for ET in 5/8 (62.5%) of the families analyzed. WES analysis in a subset of these families in our previously published study failed to identify candidate genes. In one family, we identified a deleterious and damaging variant (c.1367G>A, p.(Arg456Gln)) in the candidate gene, CACNA1G, which encodes the pore forming subunit of T-type Ca(2+) channels, CaV3.1, and is expressed in various motor pathways and has been previously implicated in neuronal autorhythmicity and ET. Other candidate genes identified include SLIT3 which encodes an axon guidance molecule and in three families, phenolyzer prioritized genes that are associated with hereditary neuropathies (family A, KARS, family B, KIF5A and family F, NTRK1). Functional studies of CACNA1G and SLIT3 suggest a role for these genes in ET disease pathogenesis. [ABSTRACT FROM AUTHOR]

Background: Schistosoma japonicum is a parasitic flatworm that causes human schistosomiasis, which is a significant cause of morbidity in China and the Philippines. A single draft genome was available for S. japonicum, yet this assembly is very fragmented and only covers 90% of the genome, which make it difficult to be applied as a reference in functional genome analysis and genes discovery. Findings: In this study, we present a high-quality assembly of the fluke S. japonicum genome by combining 20 G (~53X) long single molecule real time sequencing reads with 80 G (~ 213X) Illumina paired-end reads. This improved genome assembly is approximately 370.5 Mb, with contig and scaffold N50 length of 871.9 kb and 1.09 Mb, representing 142.4-fold and 6.2-fold improvement over the released WGS-based assembly, respectively. Additionally, our assembly captured 85.2% complete and 4.6% partial eukaryotic Benchmarking Universal Single-Copy Orthologs. Repetitive elements account for 46.80% of the genome, and 10,089 of the protein-coding genes were predicted from the improved genome, of which 96.5% have been functionally annotated. Lastly, using the improved assembly, we identified 20 significantly expanded gene families in S. japonicum, and those genes were primarily enriched in functions of proteolysis and protein glycosylation. Conclusions: Using the combination of PacBio and Illumina Sequencing technologies, we provided an improved high-quality genome of S. japonicum. This improved genome assembly, as well as the annotation, will be useful for the comparative genomics of the flukes and more importantly facilitate the molecular studies of this important parasite in the future. [ABSTRACT FROM AUTHOR]

One of the most frequently mutated proteins in human B-lineage leukemia is the transcription factor PAX5. These mutations often result in partial rather than complete loss of function of the transcription factor. While the functional dose of PAX5 has a clear connection to human malignancy, there is limited evidence for that heterozygote loss of PAX5 have a dramatic effect on the development and function of B-cell progenitors. One possible explanation comes from the finding that PAX5 mutated B-ALL often display complex karyotypes and additional mutations. Thus, PAX5 might be one component of a larger transcription factor network targeted in B-ALL. To investigate the functional network associated with PAX5 we used BioID technology to isolate proteins associated with this transcription factor in the living cell. This identified 239 proteins out of which several could be found mutated in human B-ALL. Most prominently we identified the commonly mutated IKZF1 and RUNX1, involved in the formation of ETV6-AML1 fusion protein, among the interaction partners. ChIP- as well as PLAC-seq analysis supported the idea that these factors share a multitude of target genes in human B-ALL cells. Gene expression analysis of mouse models and primary human leukemia suggested that reduced function of PAX5 increased the ability of an oncogenic form of IKZF1 or ETV6-AML to modulate gene expression. Our data reveals that PAX5 belong to a regulatory network frequently targeted by multiple mutations in B-ALL shedding light on the molecular interplay in leukemia cells. [ABSTRACT FROM AUTHOR]

Background: Circular RNAs (circRNAs) have been shown to interact with microRNAs (miRNA) as competitive endogenous RNAs (ceRNAs) to regulate target gene expression and participate in tumorigenesis. However, the role of circRNA-mediated ceRNAs in bladder cancer (BC) remains unknown. Accordingly, the aim of this study was to elucidate the regulatory mechanisms in BC based on construction of the ceRNA network. Methods: The RNA expression profiles were obtained from public datasets in the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database, and were used to establish a circRNA-miRNA-mRNA network. The interactions among proteins were analyzed using the STRING database and hubgenes were extracted using the cytoHubba application. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of differentially expressed mRNAs in BC and normal tissue samples were performed to determine the functions of the intersecting mRNAs. Results: A total of 27 circRNAs, 76 miRNAs, and 4744 mRNAs were found to be differentially expressed between BC and normal tissues. The circRNA-miRNA-mRNA ceRNA network was established based on 21 circRNAs, 14 miRNAs, and 150 mRNAs differentially expressed in BC. We also established a protein-protein interaction network and identified 10 hubgenes, which were used to construct circRNA-miRNA-hubgene regulatory modules. The most enriched biological process GO term was strand displacement (P<0.05), and the homologous recombination and Fanconi anemia pathways were significantly enriched (P<0.05) for the differentially expressed genes in BC. Conclusions: We screened several dysregulated circRNAs and established a circRNA-associated ceRNA network by bioinformatics analysis. The identified ceRNAs are likely critical in the pathogenesis of BC and may serve as future therapeutic biomarkers. [ABSTRACT FROM AUTHOR]

Previous research revealed the feline skin bacterial microbiota to be site-specific and the fungal microbiota to be individual-specific. The effect of other factors, such as genotype and environment, have not yet been studied in cats, but have been shown to be potentially important in shaping the cutaneous microbiota of other animals. Therefore, the objectives of this study were to evaluate the effect of these factors on the bacterial and fungal microbiota of feline skin and oral cavity. The influence of genotype was assessed through the analysis of different cat breeds, and the influence of environment through comparison of indoor and outdoor cats. DNA was extracted from skin and oral swabs, and bacterial and fungal next-generation sequencing were performed. Analysis of the skin microbiota of different cat breeds revealed significant differences in alpha diversity, with Sphynx and Bengal cats having the most diverse communities. Many taxa were found to be differentially abundant between cat breeds, including Veillonellaceae and Malassezia spp. Outdoor environment exposure had considerable influence on beta diversity, especially in the oral cavity, and resulted in numerous differentially abundant taxa. Our findings indicate that the oral bacterial microbiota and both fungal and bacterial microbiota of feline skin are influenced by breed, and to a lesser degree, environment. [ABSTRACT FROM AUTHOR]

The malaria mosquito, Anopheles stephensi, and other mosquitoes modulate their biology to match the time-of-day. In the present work, we used a non-hypothesis driven approach (untargeted proteomics) to identify proteins in mosquito tissue, and then quantified the relative abundance of the identified proteins from An. stephensi bodies. Using these quantified protein levels, we then analyzed the data for proteins that were only detectable at certain times-of-the day, highlighting the need to consider time-of-day in experimental design. Further, we extended our time-of-day analysis to look for proteins which cycle in a rhythmic 24-hour (“circadian”) manner, identifying 31 rhythmic proteins. Finally, to maximize the utility of our data, we performed a proteogenomic analysis to improve the genome annotation of An. stephensi. We compare peptides that were detected using mass spectrometry but are ‘missing’ from the An. stephensi predicted proteome, to reference proteomes from 38 other primarily human disease vector species. We found 239 such peptide matches and reveal that genome annotation can be improved using proteogenomic analysis from taxonomically diverse reference proteomes. Examination of ‘missing’ peptides revealed reading frame errors, errors in gene-calling, overlapping gene models, and suspected gaps in the genome assembly. [ABSTRACT FROM AUTHOR]

Aberrant DNA methylation disrupts normal gene expression in cancer and broadly contributes to oncogenesis. We previously developed MethylMix, a model-based algorithmic approach to identify epigenetically regulated driver genes. MethylMix identifies genes where methylation likely executes a functional role by using transcriptomic data to select only methylation events that can be linked to changes in gene expression. However, given that proteins more closely link genotype to phenotype recent high-throughput proteomic data provides an opportunity to more accurately identify functionally relevant abnormal methylation events. Here we present a MethylMix analysis that refines nominations for epigenetic driver genes by leveraging quantitative high-throughput proteomic data to select only genes where DNA methylation is predictive of protein abundance. Applying our algorithm across three cancer cohorts we find that using protein abundance data narrows candidate nominations, where the effect of DNA methylation is often buffered at the protein level. Next, we find that MethylMix genes predictive of protein abundance are enriched for biological processes involved in cancer including functions involved in epithelial and mesenchymal transition. Moreover, our results are also enriched for tumor markers which are predictive of clinical features like tumor stage and we find clustering using MethylMix genes predictive of protein abundance captures cancer subtypes. [ABSTRACT FROM AUTHOR]

Introduction: One of the main problems involved in heart transplantation (HT) is antibody-mediated rejection (AMR). Many aspects of AMR are still unresolved, including its etiology, diagnosis and treatment. In this project, we hypothesize that variants in genes involved in B-cell biology in HT patients can yield diagnostic and prognostic information about AMR. Methods: Genetic variants in 61 genes related to B-cell biology were analyzed by next generation sequencing in 46 HT patients, 23 with and 23 without AMR. Results: We identified 3 single nucleotide polymorphisms in ITGA4 gene (c.1845G>A, c.2633A>G, and c.2883C>T) that conformed the haplotype AGT-ITGA4. This haplotype is associated with the development of AMR. Moreover, AMR patients with the haplotype AGT-ITGA4 present lower levels of integrin α-4 in serum samples compared to the reference GAC haplotype in control patients. Conclusion: We can conclude that polymorphisms in genes related to the biology of B-cells could have an important role in the development of AMR. In fact, the AGT haplotype in ITGA4 gene could potentially increase the risk of AMR. [ABSTRACT FROM AUTHOR]