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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2019

Brain Regional Gene Expression Network Analysis Identifies Unique Interactions Between Chronic Ethanol Exposure and Consumption

Progressive increases in ethanol consumption is a hallmark of alcohol use disorder (AUD). Persistent changes in brain gene expression are hypothesized to underlie the altered neural signaling producing abusive consumption in AUD. To identify brain regional gene expression networks contributing to progressive ethanol consumption, we performed microarray and scale-free network analysis of expression responses in a C57BL/6J mouse model utilizing chronic intermittent ethanol by vapor chamber (CIE) in combination with limited access oral ethanol consumption. This model has previously been shown to produce long-lasting increased ethanol consumption, particularly when combining oral ethanol access with repeated cycles of intermittent vapor exposure. The interaction of CIE and oral consumption was studied by expression profiling and network analysis in medial prefrontal cortex, nucleus accumbens, hippocampus, bed nucleus of the stria terminalis, and central nucleus of the amygdala. Brain region expression networks were analyzed for ethanol-responsive gene expression, correlation with ethanol consumption and functional content using extensive bioinformatics studies. In all brain-regions studied the largest number of changes in gene expression were seen when comparing ethanol naive mice to those exposed to CIE and drinking. In the prefrontal cortex, however, unique patterns of gene expression were seen compared to other brain-regions. Network analysis identified modules of co-expressed genes in all brain regions. The prefrontal cortex and nucleus accumbens showed the greatest number of modules with significant correlation to drinking behavior. Across brain-regions, however, many modules with strong correlations to drinking, both baseline intake and amount consumed after CIE, showed functional enrichment for synaptic transmission and synaptic plasticity.

genomics↗

bioRxiv2019

The Drosophila fertility factor kl-3 is linked to the Y-chromosome of the vector of Chagas’ disease Triatoma infestans (Hemiptera: Reduviidae) and is essential for male fertility

In many insects, the Y chromosome plays a key role in sexual determination and male fertility. The Chagas disease vector Triatoma infestans has 22 autosomal chromosomes and a pair of XY sex chromosomes. However, the knowledge on the Y chromosome of this species, its genetic content or its biological function, is very poor. Due to repetitive DNA, Y chromosome sequences are poorly assembled in genome projects, hindering structural and functional studies on Y-linked genes. Our group has developed many of the bioinformatic tools to identify Y-linked sequences in assembled genomes. Here, we describe the identification of a {gamma}-dynein heavy chain linked to the Y-chromosome of T. infestans. This protein is orthologous to the Drosophila melanogaster Y-linked gene kl-3. In D. melanogaster, dyneins of the Y chromosome are known as male fertility factors and their deletion causes male infertility. We performed knockdown of the kl-3 expression to ascertain its function in T. infestans. Our results showed that injection of dsKL3 reduced, significantly, the fertility of T. infestans males (p<0.01). The mean number of eggs laid by the control group was 35.64 eggs/couple while the kl-3 knockdown group was of 11.82 eggs/couple (five couples did not lay any eggs). Differences in eclosion rate was even more significant, with a hatching mean rate of 16.85{+/-}10.03 and 1.69{+/-}3.58 (p<0.001) for the control and the silenced groups respectively. Our results suggest that kl-3 maintains its functional role as essential for male fertility in T. infestans. Hence, it seems that the Y-chromosome of T. infestans has a key role in male fertility. This is the first report of a kl-3 orthologue linked to the Y chromosome of an insect species outside the diptera clade. In addition to the first report of a Y-linked gene in T. infestans with a role for male fertility, this finding is of great relevance for the study of the evolution of Y chromosomes and further studies that could lead to novel approaches in insect control.

genomics↗

bioRxiv2019

Druggable genome screen identifies new regulators of the abundance and toxicity of ATXN3, the Spinocerebellar Ataxia Type 3 disease protein

BackgroundSpinocerebellar Ataxia type 3 (SCA3, also known as Machado-Joseph disease) is a neurodegenerative disorder caused by a CAG repeat expansion encoding an abnormally long polyglutamine (polyQ) tract in the disease protein, ataxin-3 (ATXN3). No preventive treatment is yet available for SCA3. Because SCA3 is likely caused by a toxic gain of ATXN3 function, a rational therapeutic strategy is to reduce mutant ATXN3 levels by targeting pathways that control its production or stability. Here, we sought to identify genes that modulate ATXN3 levels as potential therapeutic targets in this fatal disorder.\n\nMethodsWe screened a collection of siRNAs targeting 2742 druggable human genes using a cell-based assay based on luminescence readout of polyQ-expanded ATXN3. From 317 candidate genes identified in the primary screen, 100 genes were selected for validation. Among the 33 genes confirmed in secondary assays, 15 were validated in an independent cell model as modulators of pathogenic ATXN3 protein levels. Ten of these genes were then assessed in a Drosophila model of SCA3, and one was confirmed as a key modulator of physiological ATXN3 abundance in SCA3 neuronal progenitor cells.\n\nResultsAmong the 15 genes shown to modulate ATXN3 in mammalian cells, orthologs of CHD4, FBXL3, HR and MC3R regulate mutant ATXN3-mediated toxicity in fly eyes. Further mechanistic studies of one of these genes, FBXL3, encoding a F-box protein that is a component of the SKP1-Cullin-F-box (SCF) ubiquitin ligase complex, showed that it reduces levels of normal and pathogenic ATXN3 in SCA3 neuronal progenitor cells, primarily via a SCF complex-dependent manner. Bioinformatic analysis of the 15 genes revealed a potential molecular network with connections to tumor necrosis factor-/nuclear factor-kappa B (TNF/NF-kB) and extracellular signal-regulated kinases 1 and 2 (ERK1/2) pathways.\n\nConclusionsWe identified 15 druggable genes with diverse functions to be suppressors or enhancers of pathogenic ATXN3 abundance. Among identified pathways highlighted by this screen, the FBXL3/SCF axis represents a novel molecular pathway that regulates physiological levels of ATXN3 protein.

neuroscience↗

bioRxiv2019

miR-1/206 down-regulates splicing factor Srsf9 to promote myogenesis

BackgroundMyogenesis is driven by specific changes in the transcriptome that occur during the different stages of muscle differentiation. In addition to controlled transcriptional transitions, several other post-transcriptional mechanisms direct muscle differentiation. Both alternative splicing and miRNA activity regulate gene expression and production of specialized protein isoforms. Importantly, disruption of either process often results in severe phenotypes as reported for several muscle diseases. Thus, broadening our understanding of the post-transcriptional pathways that operate in muscles will lay the foundation for future therapeutic interventions.\n\nMethodsWe employed bioinformatics analysis in concert with the well-established C2C12 cell system for predicting and validating novel miR-1 and miR-206 targets engaged in muscle differentiation. We used reporter gene assays to test direct miRNA targeting and studied C2C12 cells stably expressing one of the cDNA candidates fused to a heterologous, miRNA-resistant 3 UTR. We monitored effects on differentiation by measuring fusion index, myotube area, and myogenic gene expression during time course differentiation experiments.\n\nResultsGene ontology analysis revealed a strongly enriched set of putative miR-1 and miR-206 targets associated with RNA metabolism. Notably, the expression levels of several candidates decreased during C2C12 differentiation. We discovered that the splicing factor Srsf9 is a direct target of both miRNAs during myogenesis. Persistent Srsf9 expression during differentiation impaired myotube formation and blunted induction of the early pro-differentiation factor myogenin as well as the late differentiation marker sarcomeric myosin, Myh8.\n\nConclusionsOur data uncover novel miR-1 and miR-206 cellular targets and establish a functional link between the splicing factor Srsf9 and myoblast differentiation. The finding that miRNA-mediated clearance of Srsf9 is a key myogenic event illustrates the coordinated and sophisticated interplay between the diverse components of the gene regulatory network.

cell biology↗

bioRxiv2019

Insights into the bacterial profiles and resistome structures following severe 2018 flood in Kerala, South India

Extreme flooding is one of the major risk factors for human health, and it can significantly influence the microbial communities and enhance the mobility of infectious disease agents within its affected areas. The flood crisis in 2018 was one of the severe natural calamities recorded in the southern state of India (Kerala) that significantly affected its economy and ecological habitat. We utilized a combination of shotgun metagenomics and bioinformatics approaches for understanding microbiome disruption and the dissemination of pathogenic and antibiotic-resistant bacteria on flooded sites. Here we report, altered bacterial profiles at the flooded sites having 77 significantly different bacterial genera in comparison with non-flooded mangrove settings. The flooded regions were heavily contaminated with faecal contamination indicators such as Escherichia coli and Enterococcus faecalis and resistant strains of Pseudomonas aeruginosa, Salmonella Typhi/Typhimurium, Klebsiella pneumoniae, Vibrio cholerae and Staphylococcus aureus. The resistome of the flooded sites contains 103 resistant genes, of which 38% are encoded in plasmids, where most of them are associated with pathogens. The presence of 6 pathogenic bacteria and its susceptibility to multiple antibiotics including ampicillin, chloramphenicol, kanamycin and tetracycline hydrochloride were confirmed in flooded and post-flooded sites using traditional culture-based analysis followed by 16S rRNA sequencing. Our results reveal altered bacterial profile following a devastating flood event with elevated levels of both faecal contamination indicators and resistant strains of pathogenic bacteria. The circulation of raw sewage from waste treatment settings and urban area might facilitate the spreading of pathogenic bacteria and resistant genes.

microbiology↗

bioRxiv2019

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling

Microbial community profiles have been associated with a variety of traits, including methane emissions in livestock, however, these profiles can be difficult and expensive to obtain for thousands of samples. The objective of this work was to develop a low-cost, high-throughput approach to capture the diversity of the rumen microbiome. Restriction enzyme reduced representation sequencing (RE-RRS) using ApeKI or PstI, and two bioinformatic pipelines (reference-based and reference-free) were compared to 16S rRNA gene sequencing using repeated samples collected two weeks apart from 118 sheep that were phenotypically extreme (60 high and 58 low) for methane emitted per kg dry matter intake (n=236). DNA was extracted from freeze-dried rumen samples using a phenol chloroform and bead-beating protocol prior to sequencing. The resulting sequences were used to investigate the repeatability of the rumen microbial community profiles, the effect of host genetics, laboratory and analytical method, and the genetic and phenotypic correlations with methane production. The results suggested that the best method was PstI RE-RRS analyzed with the reference-free approach via a correspondence analysis, with estimates for repeatability of 0.62{+/-}0.06, heritability 0.31{+/-}0.29, and genetic and phenotypic correlation with methane emissions of 0.88{+/-}0.25 and 0.64{+/-}0.05 respectively for the first component of correspondence analysis. The reference-free approach assigned 62.0{+/-}5.7% of reads to common 65 bp tags, much higher than the reference-based approach of 6.8{+/-}1.8% of reads assigned. Sensitivity studies suggested approximately 2000 samples could be sequenced in a single lane on an Illumina HiSeq 2500, therefore the current work of 118 samples/lane and future proposed 384 samples/lane are well within that threshold. Our approach is now being used to investigate host factors affecting the rumen and its association with a variety of production and environmental traits. With minor adaptations, our approach could be used to obtain microbial profiles from other metagenomic samples.

microbiology↗

bioRxiv2019

Conservation of gene architecture and domains amidst sequence divergence in the hsrω lncRNA gene across the Drosophila genus

The developmentally active and cell-stress responsive hsr{omega} locus in Drosophila melanogaster carries two exons, one omega intron, one short translatable open reading frame ORF{omega}, long stretch of unique tandem repeats and an overlapping mir-4951 near its 3 end. It produces multiple lncRNAs using two transcription start and four termination sites. Earlier studies revealed functional conservation in several Drosophila species but with little sequence conservation, in three experimentally examined species, of ORF{omega}, tandem repeat and other regions but ultra-conservation of 16nt at 5 and 60nt at 3 splice-junctions of the omega intron. Present bioinformatic study, using the splice-junction landmarks in Drosophila melanogaster hsr{omega}, identified orthologues in publicly available 34 Drosophila species genomes. Each orthologue carries the short ORF{omega}, ultra-conserved splice junctions of omega intron, repeat region, conserved 3-end located mir-4951, and syntenic neighbours. Multiple copies of conserved nonamer motifs are seen in the tandem repeat region, despite a high variability in repeat sequences. Intriguingly, only the intron sequences in different species show evolutionary relationships matching the general phylogenetic history in the genus. Search in other known insect genomes did not reveal sequence homology although a locus with similar functional properties is suggested in Chironomus and Ceratitis species. Amidst the high sequence divergence, the conserved organization of exons, ORF{omega} and omega intron in this genes proximal part and tandem repeats in distal part across the Drosophila genus is remarkable and possibly reflects functional importance of higher order structure of hsr{omega} lncRNAs and the small Omega peptide.

genomics↗

bioRxiv2019

A comprehensive dataset of TLX1 positive ALL-SIL lymphoblasts and primary T-cell acute lymphoblastic leukemias

Most currently available transcriptome data of T-cell acute lymphoblastic leukemia (T-ALL) are based on polyA[+] RNA sequencing methods thus lacking non-polyadenylated transcripts. Here, we present the data of polyA[+] and total RNA sequencing in the context of in vitro TLX1 knockdown in ALL-SIL cells and a primary T-ALL cohort. We extended this dataset with ATAC sequencing and H3K4me1 and H3K4me3 ChIP sequencing data to map putative gene regulatory regions. In this data descriptor, we present a detailed report of how the data were generated and which bioinformatics analyses were performed. Through several technical validations, we showed that our sequencing data are of high quality and that our in vitro TLX1 knockdown was successful. We also validated the quality of the ATAC and ChIP sequencing data and showed that ATAC and H3K4me3 ChIP peaks are enriched at transcription start sites. We believe that this comprehensive set of sequencing data can be reused by others to further unravel the complex biology of T-ALL in general and TLX1 in particular.

molecular biology↗

bioRxiv2019

Human induced pluripotent stem cell-derived neuroectodermal epithelial cells mistaken for blood-brain barrier-forming endothelial cells

Brain microvascular endothelial cells (BMECs) possess unique properties underlying the blood-brain-barrier (BBB), that are crucial for homeostatic brain functions and interactions with the immune system. Modulation of BBB function is essential for treatment of neurological diseases and effective tumor targeting. Studies to-date have been hampered by the lack of physiological models using cultivated human BMECs that sustain BBB properties. Recently, differentiation of induced pluripotent stem cells (iPSCs) into cells with BBB-like properties has been reported, providing a robust in vitro model for drug screening and mechanistic understanding of neurological diseases. However, the precise identity of these iBMECs remains unclear. Employing single-cell RNA sequencing, bioinformatic analysis and immunofluorescence for several pathways, transcription factors (TFs), and surface markers, we examined the molecular and functional properties of iBMECs differentiated either in the absence or presence of retinoic acid. We found that iBMECs lack both endothelial-lineage genes and ETS TFs that are essential for the establishment and maintenance of EC identity. Moreover, iBMECs fail to respond to angiogenic stimuli and form lumenized vessels in vivo. We demonstrate that human iBMECs are not barrier-forming ECs but rather EpCAM+ neuroectodermal epithelial cells (NE-EpiCs) that form tight junctions resembling those present in BBB-forming BMECs. Finally, overexpression of ETS TFs (ETV2, FLI1, and ERG) reprograms NE-EpiCs to become more like the BBB-forming ECs. Thus, although directed differentiation of human iBMECs primarily gives rise to epithelial cells, overexpression of several ETS TFs can divert them toward a vascular BBB in vitro.

cell biology↗

bioRxiv2019

Novel tetraplex qPCR assays for simultaneous detection and identification of Xylella fastidiosa subspecies in plant tissues

Xylella fastidiosa is an insect-borne bacterium confined to the xylem vessels of plants. This plant pathogen has a broad host range estimated to 560 plant species. Five subspecies of the pathogen with different but overlapping host ranges have been described, but only three subspecies are widely accepted, namely subspecies fastidiosa, multiplex and pauca. Initially limited to the Americas, Xf has been detected in Europe since 2013. As management of X. fastidiosa outbreaks in Europe depends on the identification of the subspecies, accurate determination of the subspecies in infected plants as early as possible is of major interest. Thus, we developed various tetraplex and triplex qPCR assays for Xylella fastidiosa detection and subspecies identification in planta in a single reaction. We designed primers and probes using SkIf, a bioinformatics tool based on k-mers, to detect specific signatures of the species and subspecies from a dataset of 58 genome sequences representative of X. fastidiosa diversity. We tested the qPCR assays on 39 target and 30 non-target strains, as well as on 13 different plant species spiked with strains of the different subspecies of X. fastidiosa, and on samples from various environmental and inoculated host plants. Sensitivity of simplex assays was equal or slightly better than the reference protocol on purified DNA. Tetraplex qPCR assays had the same sensitivity than the reference protocol and allowed X. fastidiosa detection in all spiked matrices up to 103 cells.mL-1. Moreover, mix infections of two to three subspecies could be detected in the same sample with tetraplex assays. In environmental plant samples, the tetraplex qPCR assays allowed subspecies identification when the current method based on multilocus sequence typing failed. The qPCR assays described here are robust and modular tools that are efficient for differentiating X. fastidiosa subspecies directly in plant samples.

molecular biology↗

bioRxiv2019

Nucleosome scaffolding by Brd4 tandem bromodomains in acetylation-dependent chromatin compartmentalization

Bromodomain binding of acetyl-lysine residues is a crucial step in many epigenetic mechanisms governing transcription. Nearly half of human bromodomains exist in tandem with at least one other bromodomain on a single protein. The Bromodomain and ExtraTerminal domain (BET) familyof proteins (BrdT, Brd2, Brd3 and Brd4) each encode two bromodomains at their N-termini and are important regulators of acetylation-dependent transcription in homeostasis and disease. Previous efforts have focused on identifying protein acetylation sites bound by individual bromodomains. However, the mechanisms through which tandem bromodomains act cooperatively on chromatin are largely unknown. Here, we first used small angle x-ray scattering combined with Rosetta ab initio modeling to explore conformational space available to BET tandem bromodomains. For Brd4, the flexible tandem bromodomain linker allows for distances between the two acetyl-lysine binding sites ranging from 15 to 157 [A]. Using a bioluminescence resonance energy transfer assay, we show a clear distance dependence for Brd4 tandem bromodomain bivalent binding of multiply acetylated histone H4 peptides. However, isothermal titration calorimetry studies revealed Brd4 binding affinity toward multiply acetylated peptides does not correlate with the potential for bivalent binding. We used sucrose gradient assays to provide direct evidence in vitro that Brd4 tandem bromodomains can simultaneously bind and scaffold multiple acetylated nucleosomes. Intriguingly, our bioinformatic analysis of deposited chromatin immunoprecipitation sequencing data indicates that Brd4 colocalizes with subsets of histone acetyl-lysine sites across transcriptionally active chromatin compartments. These findings support our hypothesis that scaffolding of acetylated nucleosomes by Brd4 tandem bromodomains contributes to higher-order chromatin architecture.

biochemistry↗

bioRxiv2019

Direct Metatranscriptome RNA-seq and Multiplex RT-PCR Amplicon Sequencing on Nanopore MinION - Promising Strategies for Multiplex Identification of Viable Pathogens in Food

Viable pathogenic bacteria are major biohazards that pose a significant threat to food safety. Despite the recent developments in detection platforms, multiplex identification of viable pathogens in food remains a major challenge. A novel strategy is developed through direct metatranscriptome RNA-seq and multiplex RT-PCR amplicon sequencing on Nanopore MinION to achieve real-time multiplex identification of viable pathogen in food. Specifically, this study reports an optimized universal Nanopore sample extraction and library preparation protocol applicable to both Gram-positive and Gram-negative pathogenic bacteria, demonstrated using a cocktail culture of E. coli O157:H7, Salmonella enteritidis, and Listeria monocytogenes, which were selected based on their impact on economic loss or prevalence in recent outbreaks. Further evaluation and validation confirmed the accuracy of direct metatranscriptome RNA-seq and multiplex RT-PCR amplicon sequencing using Sanger sequencing and selective media. The study also included a comparison of different bioinformatic pipelines for metatranscriptomic and amplicon genomic analysis. MEGAN without rRNA mapping showed the highest accuracy of multiplex identification using the metatranscriptomic data. EPI2ME also demonstrated high accuracy using multiplex RT-PCR amplicon sequencing. In addition, a systemic comparison was drawn between Nanopore sequencing of the direct metatranscriptome RNA-seq and RT-PCR amplicons. Both methods are comparable in accuracy and time. Nanopore sequencing of RT-PCR amplicon has higher sensitivity, but Nanopore metatranscriptome sequencing excels in read length and dealing with complex microbiome and non-bacterial transcriptome backgrounds. To the best of our knowledge, this is the first report of metatranscriptome sequencing of cocktail microbial RNAs on the emerging Nanopore platform. Direct RNA-seq and RT-PCR amplicons sequencing of metatranscriptome enable the direct identification of nucleotide analogs in RNAs, which is highly informative for determining microbial identities while detecting ecologically relevant processes. The information pertained in this study could be important for future revelatory research, including predicting antibiotic resistance, elucidating host-pathogen interaction, prognosing disease progression, and investigating microbial ecology, etc.

microbiology↗

bioRxiv2019

SID-4/NCK-1 is important for dsRNA import in Caenorhabditis elegans

RNA interference (RNAi) is sequence-specific gene silencing triggered by double-stranded (ds)RNA. When dsRNA is expressed or introduced into one cell and is transported to and initiates RNAi in other cells, it is called systemic RNAi. Systemic RNAi is very efficient in C. elegans and genetic screens for systemic RNAi defective (Sid) mutants have identified RNA transporters (SID-1, SID-2 and SID-5) and a signaling protein (SID-3). Here we report that SID-4 is nck-1, a C. elegans NCK-like adaptor protein. sid-4 null mutations cause a weak, dosesensitive, systemic RNAi defect and can be effectively rescued by SID-4 expression in target tissues only, implying a role in dsRNA import. SID-4 and SID-3 (ACK-1 kinase) homologs interact in mammals and insects, suggesting they may function in a common signaling pathway, however, a sid-3; sid-4 double mutants showed additive resistance to RNAi, suggesting that these proteins likely interact with other signaling pathways as well. A bioinformatic screen coupled to RNAi sensitivity tests identified 23 additional signaling components with weak RNAi defective phenotypes. These observations suggest that environmental conditions may modulate systemic RNAi efficacy, and indeed, sid-3 and sid-4 are required for growth temperature effects on systemic RNAi silencing efficiency.

genetics↗

bioRxiv2019

Universal Deep Sequence Models for Protein Classification

MotivationInferring the properties of a protein from its amino acid sequence is one of the key problems in bioinformatics. Most state-of-the-art approaches for protein classification tasks are tailored to single classification tasks and rely on handcrafted features such as position-specific-scoring matrices from expensive database searches. We argue that this level of performance can be reached or even be surpassed by learning a task-agnostic representation once, using self-supervised language modeling, and transferring it to specific tasks by a simple finetuning step.\n\nResultsWe put forward a universal deep sequence model that is pretrained on unlabeled protein sequences from Swiss-Prot and finetuned on protein classification tasks. We apply it to three prototypical tasks, namely enzyme class prediction, gene ontology prediction and remote homology and fold detection. The proposed method performs on par with state-of-the-art algorithms that were tailored to these specific tasks or, for two out of three tasks, even outperforms them. These results stress the possibility of inferring protein properties from the sequence alone and, on more general grounds, the prospects of modern natural language processing methods in omics.\n\nAvailabilitySource code is available under https://github.com/nstrodt/UDSMProt.\n\nContactfirstname.lastname@hhi.fraunhofer.de

synthetic biology↗

bioRxiv2019

Liver X Receptor activation regulates genes involved in lipid homeostasis in developing chondrocytes

ObjectiveOsteoarthritis (OA) is the most common type of arthritis and causes debilitating symptoms and decreased quality of life. Currently available treatment options target symptoms but do not address the underlying issue of joint tissue degeneration. As such, a better understanding of the molecular mechanisms maintaining cartilage health is needed for developing novel therapeutic strategies. Liver X Receptors (LXRs) are nuclear receptors that have been previously shown to offer protection against OA. This is potentially due to suppression of chondrocyte hypertrophy in endochondral bone growth in response to LXR activation. In order to better understand the regulatory mechanisms behind this effect, we aimed to systematically examine LXRs effects on growth plate chondrocyte gene expression.\n\nMethodsPrimary chondrocytes isolated from the long bones of E15.5 mice were treated with the specific LXR agonist, GW3965, and RNA was isolated for Affymetrix microarrays followed by real time qPCR validation. Bioinformatics analyses were performed using Gene Ontology (GO) and KEGG pathway analysis. Immunohistochemistry was conducted to examine protein localization of LXR and identified targets in GW3965-treated E15.5 tibiae compared to control.\n\nResultsActivation of LXR in primary growth plate chondrocytes resulted in differential regulations of various genes involved in lipid metabolism, including several genes involved in cholesterol efflux. This pattern was compared to LXR activation in immature murine articular chondrocytes (IMACs), which revealed similar roles in lipid homeostasis. Immunohistochemical analysis of LXR and its identified targets Abca1 and Srebf1 revealed preferential protein localization to pre-hypertrophic and resting chondrocytes in GW3965-treated tibial growth plates compared to controls.\n\nConclusionOur findings show for the first time that LXR activation alters expression of lipid metabolism genes in growth plate chondrocytes, in part through activation of molecules responsible for cellular cholesterol efflux. This provides insight into potential mechanisms through which LXR regulates cellular metabolism to alter chondrocyte behavior and phenotype.

physiology↗

bioRxiv2019

Population structure determined by comparative amplicon gene sequencing in biofilm and planktonic bacterial communities from pesticide-contaminated water

Molecular and bioinformatics tools for research are very important for biodiversity characterization in contaminated environments due the presence of a high percentage of nonculturable microorganisms. The wide use of pesticides in agriculture exposes microbiomes to stressful and selective conditions that demand survival strategies such as biofilm formation. The purpose of this work was to evaluate the bacterial population structure in planktonic and biofilm communities of water that was used for washing the packaging of herbicides and stored for six months in tanks. This substance is highly contaminated waste. Samples of water and biofilms from tanks and biofilms developed for short times in flasks were used for DNA isolation and 16S rRNA gene sequencing. The physicochemical conditions imposed by water used for washing the containers were inadequate for killing the bacterial genera identified according to water and wastewater standards. The variation in population structure and diversity was lower in the planktonic samples than in the biofilm samples, indicating a possible combination of genetic drift and subsequent selection of individuals surviving under stressful water conditions, such as heating and contact with agrochemicals, over a six-month period. The biofilm formation in water tanks contaminated with pesticides enabled the survival of bacterial genera harboring the essential processes for adaptation to these environments; the presence of these processes was determined according to descriptions obtained from the genomic databases. This study suggests the potential of bacterial genera identified in biofilms obtained from tanks to adapt to contaminated environments through their metabolic complexity. Thus, herbicide biodegradation kinetics can be accessed through a culturable collection obtained from these communities.

microbiology↗

bioRxiv2019

Prioritization of genes driving congenital phenotypes of patients with de novo genomic structural variants

BackgroundGenomic structural variants (SVs) can affect many genes and regulatory elements. Therefore, the molecular mechanisms driving the phenotypes of patients with multiple congenital abnormalities and/or intellectual disability carrying de novo SVs are frequently unknown.\n\nResultsWe applied a combination of systematic experimental and bioinformatic methods to improve the molecular diagnosis of 39 patients with de novo SVs and an inconclusive diagnosis after regular genetic testing. In seven of these cases (18%) whole genome sequencing analysis detected disease-relevant complexities of the SVs missed in routine microarray-based analyses. We developed a computational tool to predict effects on genes directly affected by SVs and on genes indirectly affected due to changes in chromatin organization and impact on regulatory mechanisms. By combining these functional predictions with extensive phenotype information, candidate driver genes were identified in 16/39 (41%) patients. In eight cases evidence was found for involvement of multiple candidate drivers contributing to different parts of the phenotypes. Subsequently, we applied this computational method to a collection of 382 patients with previously detected and classified de novo SVs and identified candidate driver genes in 210 cases (54%), including 32 cases whose SVs were previously not classified as pathogenic. Pathogenic positional effects were predicted in 25% of the cases with balanced SVs and in 8% of the cases with copy number variants.\n\nConclusionsThese results show that driver gene prioritization based on integrative analysis of WGS data with phenotype association and chromatin organization datasets can improve the molecular diagnosis of patients with de novo SVs.

genomics↗

bioRxiv2019

PyIOmica: Longitudinal Omics Analysis and Classification

SummaryPyIOmica is an open-source Python package focusing on integrating longitudinal multiple omics datasets, characterizing, and classifying temporal trends. The package includes multiple bioinformatics tools including data normalization, annotation, classification, visualization, and enrichment analysis for gene ontology terms and pathways. Additionally, the package includes an implementation of visibility graphs to visualize time series as networks.\n\nAvailability and implementationPyIOmica is implemented as a Python package (pyiomica), available for download and installation through the Python Package Index (PyPI) (https://pypi.python.org/pypi/pyiomica), and can be deployed using the Python import function following installation. PyIOmica has been tested on Mac OS X, Unix/Linux and Microsoft Windows. The application is distributed under an MIT license. Source code for each release is also available for download on Zenodo (https://doi.org/10.5281/zenodo.3342612).\n\nContactgmias@msu.edu

systems biology↗