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Results for “molecular biology”

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bioRxiv2019

A rapid and accurate MinION-based workflow for tracking species biodiversity in the field

Genetic markers (DNA barcodes) are often used to support and confirm species identification. Barcode sequences can be generated in the field using portable systems based on the Oxford Nanopore Technologies (ONT) MinION platform. However, to achieve a broader application, current proof-of-principle workflows for on-site barcoding analysis must be standardized to ensure reliable and robust performance under suboptimal field conditions without increasing costs. Here we demonstrate the implementation of a new on-site workflow for DNA extraction, PCR-based barcoding and the generation of consensus sequences. The portable laboratory features inexpensive instruments that can be carried as hand luggage and uses standard molecular biology protocols and reagents that tolerate adverse environmental conditions. Barcodes are sequenced using MinION technology and analyzed with ONTrack, an original de novo assembly pipeline that requires as few as 500 reads per sample. ONTrack-derived consensus barcodes have high accuracy, ranging from 99,8% to 100%, despite the presence of homopolymer runs. The ONTrack pipeline has a user-friendly interface and returns consensus sequences in minutes. The remarkable accuracy and low computational demand of the ONTrack pipeline, together with the inexpensive equipment and simple protocols, make the proposed workflow particularly suitable for tracking species under field conditions.

genomics↗

bioRxiv2019

Using Deep Learning to Annotate the Protein Universe

Understanding the relationship between amino acid sequence and protein function is a long-standing problem in molecular biology with far-reaching scientific implications. Despite six decades of progress, state-of-the-art techniques cannot annotate 1/3 of microbial protein sequences, hampering our ability to exploit sequences collected from diverse organisms. In this paper, we explore an alternative methodology based on deep learning that learns the relationship between unaligned amino acid sequences and their functional annotations across all 17929 families of the Pfam database. Using the Pfam seed sequences we establish rigorous benchmark assessments that use both random and clustered data splits to control for potentially confounding sequence similarities between train and test sequences. Using Pfam full, we report convolutional networks that are significantly more accurate and computationally efficient than BLASTp, while learning sequence features such as structural disorder and transmembrane helices. Our model co-locates sequences from unseen families in embedding space, allowing sequences from novel families to be accurately annotated. These results suggest deep learning models will be a core component of future protein function prediction tools.

bioinformatics↗

bioRxiv2019

A simple and sensitive SYBR Gold-based assay to quantify DNA-protein interactions

A simple, accessible, and inexpensive assay to quantify the strength of DNA-protein interactions was developed. The assay relies on capturing DNA-protein complexes using an affinity resin that binds tagged, recombinant proteins. Sequential washes with filtration spin cups and centrifugation remove non-specific interactions in a gentle, uniform manner and a final elution isolates specific DNA-protein complexes. SYBR Gold nucleic acid stain is added to the eluted product and the fluorescence intensity accurately quantifies the amount of captured DNA, ultimately illustrating the relative strength of the DNA-protein interaction. The major utility of the assay resides in the versatility and quantitative nature of the SYBR Gold:nucleic acid interaction, eliminating the need for customized or labeled oligos and permitting relatively inexpensive quantification of binding capacity. The assay also employs DNA-protein complex capture by the very common purification tag, 6xHis, but other tags could likely be utilized. Further, SYBR Gold fluorescence is compatible with a wide variety of instruments, including UV transilluminators, a staple to any molecular biology laboratory. This assay was used to compare the binding capacities of different Auxin Response Factor (ARF) transcription factors to various dsDNA targets, including the classical AuxRE motif and several divergent sequences. Results from dose-response assays suggest that different ARF proteins might show distinct comparative affinities for AuxRE variants, emphasizing that specific ARF-AuxRE binding strengths likely contribute to the complex and fine-tuned cellular auxin response.

plant biology↗

bioRxiv2019

Oxytocin, Compulsion and Epilepsy: Insights from a Complex Behavioral and Neuronal Networks Association

Previously we have demonstrated that microinjection of oxytocin (OT) into the central nucleus of amygdala (CeA) induces hypergrooming in Wistar rats, a model of compulsion. The Wistar Audiogenic Rat (WAR) strain is a genetic model of generalized tonic-clonic seizures. Here we quantified grooming behavior in WAR, with grooming scores, flowcharts and directed graphs of syntactic and non-syntactic grooming chains, after bilateral administration of OT or saline (SAL) into the CeA and investigated the association between hypergrooming and imunohistochemistry of Fos activated compulsion networks and proposing a computational model of grooming behavior. The activated networks, driven from a CeA OT-dependent grooming pattern, in both Wistar and WAR were detected as Fos+ regions: orbitofrontal cortex, striatum, paraventricular nucleus of the hypothalamus, dentate gyrus, substantia nigra compacta and reticulata. In conclusion we can drive hypergrooming in WARs, defined previously as a model of ritualistic motor behavior in Wistar rats, with OT from CeA, a limbic structure and one of the principal amygdala complex outputs. Furthermore, our current pioneer behavioral and cellular description considers that hypergrooming (compulsion) in WARs is a comorbidity because: (1) WARs have the highest grooming scores, when exposed only to novelty (2) WARs have better grooming scores than Wistars after CeA-SAL, (3) WARs perform much better than Wistars in OT-CeA-dependent highly stereotyped behavioral sequences, detected by flowcharts as a combination of syntactic/non-syntactic grooming chains, (4) the behavioral sequences here demonstrated for grooming and hypergrooming can be modeled as quite reliable Markov chains and (5) with the exception of CeA-SAL injected animals, an exquisite map of brain Fos expression was detected in typical cortico-striatal-thalamic-basal ganglia-cortical circuit, among new areas, driven by OT-CeA.\n\nAuthor SummaryGrooming is a complex set of regular behavioral sequences in rodents that can be mimicked with several pharmacological or molecular biology interventions. We have demonstrated previously that microinjection of the brain peptide oxytocin into the amygdala, a limbic region, induces hypergrooming in Wistar rats, a model of compulsion. The Wistar Audiogenic Rat strain is a genetic model of generalized seizures, in fact a model of epilepsy. Here we quantified grooming behavior in Wistar Audiogenic Rats, using several behavioral tools such as grooming scores, behavioral sequences and graphs of grooming chains, after bilateral administration of the oxytocin or its control (saline) into the amygdala. We also investigated the association between hypergrooming and activation of compulsion networks, proposing a computational (virtual) model of grooming behavior. Basically we were able to detect activated networks, driven from amygdala and the consequent oxytocin-dependent grooming pattern in epileptic and control animals. Those circuits are composed of cortical and subcortical areas, usually associated to the expression of motor rituals or compulsions. In conclusion, we can drive hypergrooming in epileptic animals, as compared to the previously defined model of ritualistic/compulsive motor behavior in control, rats. We concluded that hypergrooming (compulsion) is endogenously present in epileptic animals as a co-existent event (comorbidity), because when they were exposed to novelty, they express better grooming scores than control animals. The behavioral sequences here demonstrated for grooming and hypergrooming can be simulated as chains, where associations can be predicted from probabilities. Finally, an exquisite map of brain-activated cells was detected in both epileptic animal and their controls, in typical cortico-subcortical structures associated with rituals, but driven from a region which control emotions.

neuroscience↗

bioRxiv2019

Not just BLAST nt: WGS database joins the party

Since its introduction in 1990 and with over 50k citations, the NCBI BLAST family has been an essential tool of in silico molecular biology. The BLAST nt database, based on the traditional divisions of GenBank, has been the default and most comprehensive database for nucleotide BLAST searches and for taxonomic classification software in metagenomics. Here we argue that this is no longer the case. Currently, the NCBI WGS database contains one billion reads (almost five times more than GenBank), and with 4.4 trillion nucleotides, WGS has about 14 times more nucleotides than GenBank. This ratio is growing with time. We advocate a change in the database paradigm in taxonomic classification by systematically combining the nt and WGS databases in order to boost taxonomic classifiers sensitivity. We present here a case in which, by adding WGS data, we obtained over five times more classified reads and with a higher confidence score. To facilitate the adoption of this approach, we provide the draftGenomes script.\n\nAuthor summaryCulture-independent methods are revolutionizing biology. The NIH/NCBI Basic Local Alignment Search Tool (BLAST) is one of the most widely used methods in computational biology. The BLAST nt database has become a de facto standard for taxonomic classifiers in metagenomics. We believe that it is time for a change in the database paradigm for such a classification. We advocate the systematic combination of the BLAST nt database with genomes of the massive NCBI Whole-Genome Shotgun (WGS) database. We make draftGenomes available, a script that eases the adoption of this approach. Current developments and technologies make it feasible now. Our recent results in several metagenomic projects indicate that this strategy boosts the sensitivity in taxonomic classifications.

bioinformatics↗

bioRxiv2019

High-yield fabrication of DNA and RNA scaffolds for single molecule force and torque spectroscopy experiments.

Single molecule biophysics experiments have enabled the observation of biomolecules with a great deal of precision in space and time, e.g. nucleic acids mechanical properties and protein-nucleic acids interactions using force and torque spectroscopy techniques. The success of these experiments strongly depends on the capacity of the researcher to design and fabricate complex nucleic acid scaffolds, as the pertinence and the yield of the experiment strongly depend on the high quality and purity of the final scaffold. Though the molecular biology techniques involved are well known, the fabrication of nucleic acids scaffold for single molecule experiments still remains a difficult task. Here, we present new protocols to generate high quality coilable double-stranded DNA and RNA, as well as DNA and RNA hairpins with ~500-1000 bp long stems. Importantly, we present a new approach based on single-stranded DNAs annealing and show, using magnetic tweezers, that it is more efficient to generate complex nucleic acid scaffolds in larger amount and at higher purity than a standard PCR-digestion-ligation approach. The protocols we describe here enable the design of any sort of complex nucleic acid scaffold for single molecule biophysics experiments and will therefore be extremely valuable to the community.

biophysics↗

bioRxiv2019

Disruption of a RAC1-centred protein interaction network is associated with Alzheimer’s disease pathology and causes age-dependent neurodegeneration

The molecular biological mechanisms of Alzheimers disease (AD) involve disease-associated cross-talk through many genes and include a loss of normal as well as a gain of abnormal interactions among genes. A protein domain network (PDN) is a collection of physical bindings that occur between protein domains, and the states of the PDNs in patients with AD are likely to be perturbed compared to those in normal healthy individuals. To identify PDN changes that cause neurodegeneration, we analysed the PDNs that occur among genes co-expressed in each of three brain regions at each stage of AD. Our analysis revealed that the PDNs collapsed with the progression of AD stage and identified five hub genes, including Rac1, as key players in PDN collapse. Using publicly available gene expression data, we confirmed that the mRNA expression level of the RAC1 gene was downregulated in the entorhinal cortex (EC) of AD brains. To test the causality of these changes in neurodegeneration, we utilized Drosophila as a genetic model and found that modest knockdown of Rac1 in neurons was sufficient to cause age-dependent behavioural deficits and neurodegeneration. Finally, we identified a microRNA, hsa-miR-101-3p, as a potential regulator of RAC1 in AD brains. As the Braak neurofibrillary tangle (NFT) stage progressed, the expression levels of hsa-miR-101-3p were upregulated specifically in the EC. Furthermore, overexpression of hsa-miR-101-3p in the human neuronal cell line SH-SY5Y caused RAC1 downregulation. These results highlight the utility of our integrated network approach for identifying causal changes leading to neurodegeneration in AD.

genomics↗

bioRxiv2019

Monotonous behavior with 2-propanol converts into reentrant transition with 1-propanol: Higher-order structure of DNA

In the present study, we measured the changes in the higher-order structure of genomic DNA molecules in the presence of alcohols through single-DNA observation by use of fluorescence microscopy, with particular focus on the different effects of 1-propanol and 2-propanol. The results showed that, with an increasing concentration of 1-propanol, DNA exhibits reentrant conformational transitions from an elongated coil to a folded globule, and then to an unfolded state. On the other hand, with 2-propanol, DNA exhibits monotonous shrinkage into a compact state. Thus, DNA molecules are more effectively condensed/precipitated with 2-propanol than with 1-propanol. The propanol isomers also had different effects on the changes in the secondary structure of DNA, as revealed by circular dichroism (CD) measurements. With 1-propanol, DNA maintains a B-form secondary structure. An A-like conformation appears with the addition of 2-propanol.\n\nSTATEMENT OF SIGNIFICANCECurrently, 2-propanol has most often been used as the solvent to extract and purify genomic DNA molecules from living cells, according the protocols in molecular biology and biochemistry. Unfortunately, the reason why usage of 2-propanol is recommended instead of ethanol and 1-propanol has never been explained in a clear manner. We believe that the new insight based on chemical physics point of view would play an important role for the development of current chemical procedures/treatments adapted on an empirical basis.

biophysics↗

bioRxiv2019

AtDAT1 is a key enzyme of D-amino acid stimulated ethylene production in Arabidopsis thaliana

D-enantiomers of proteinogenic amino acids (D-AAs) are found ubiquitously, but the knowledge about their metabolism and functions in plants is scarce. A long forgotten phenomenon in this regard is the D-AA-stimulated ethylene production in plants. As a starting point to investigate this effect the Arabidopsis accession Landsberg erecta (Ler) got into focus as it was found defective in metabolizing D-AAs. Combining genetics and molecular biology of T-DNA lines and natural variants together with biochemical and physiological approaches we could identify AtDAT1 as a major D-AA transaminase in Arabidopsis. Atdat1 loss-of-function mutants and Arabidopsis accessions with defective AtDAT1 alleles were not able to produce D-Ala, D-Glu and L-Met, the metabolites of D-Met, anymore. This result corroborates the biochemical characterization of AtDAT1, which showed highest activity using D-Met as substrate. Germination of seedlings in light and dark led to enhanced growth inhibition of atdat1 mutants on D-Met. Ethylene measurements revealed an enhanced D-AA stimulated ethylene production in these mutants. According to initial working models of this phenomenon D-Met is preferentially malonylated instead of the ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC). This decrease of ACC degradation should then lead to the increase of ethylene production. We could observe in our studies a reciprocal relation of malonylated methionine and ACC upon D-Met application and even significantly more malonyl-methionine in atdat1 mutants. Unexpectedly, the malonyl-ACC levels did not differ between mutants and wild type in these experiments. With AtDAT1, the first central enzyme of plant D-AA metabolism was characterized biochemically and physiologically. The specific effects of D-Met on ACC metabolization, ethylene production and plant development of dat1 mutants unraveled the impact of AtDAT1 on these processes, but they are not in full accordance to previous working models. Instead, our results imply the influence of additional candidate factors or processes on D-AA-stimulated ethylene production which await to be uncovered.

plant biology↗

bioRxiv2019

A highly parallel, automated platform enabling individual or sequential ChIP of histone marks and transcription factors

Despite its popularity, chromatin immunoprecipitation followed by sequencing (ChIP-seq) remains a tedious (>2d), manually intensive, low-sensitivity and low-throughput approach. Here, we combine principles of microengineering, surface chemistry and molecular biology to address the major limitations of standard ChIP-seq. The resulting approach, FloChIP, automates and miniaturizes ChIP in a beadless fashion while facilitating the downstream library preparation process through on-chip chromatin tagmentation. FloChIP is fast (<2h), has a wide dynamic range (from 106 to 500 cells), is high-throughput (up to 64 parallel, antibody- or sample-multiplexed experiments) and is compatible with both histone mark and transcription factor ChIP. In addition, FloChIPs interconnected design allows for straightforward chromatin re-immunoprecipitation, thus constituting the first example of a microfluidic sequential ChIP-seq system. Finally, we demonstrate FloChIPs high-throughput capacity by performing ChIP-seq of the transcription factor MEF2A in 32 distinct human lymphoblastoid cell lines, providing novel insights into the main factors driving collaborative DNA binding of MEF2A and into its role in B-cell-specific gene regulation. Together, our results validate FloChIP as a flexible and reproducible automated solution for individual or sequential ChIP-seq.

bioengineering↗

bioRxiv2019

openTSNE: a modular Python library for t-SNE dimensionality reduction and embedding

SummaryPoint-based visualisations of large, multi-dimensional data from molecular biology can reveal meaningful clusters. One of the most popular techniques to construct such visualisations is t-distributed stochastic neighbor embedding (t-SNE), for which a number of extensions have recently been proposed to address issues of scalability and the quality of the resulting visualisations. We introduce openTSNE, a modular Python library that implements the core t-SNE algorithm and its extensions. The library is orders of magnitude faster than existing popular implementations, including those from scikit-learn. Unique to openTSNE is also the mapping of new data to existing embeddings, which can surprisingly assist in solving batch effects.\n\nAvailabilityopenTSNE is available at https://github.com/pavlin-policar/openTSNE.\n\nContactpavlin.policar@fri.uni-lj.si, blaz.zupan@fri.uni-lj.si

bioinformatics↗

bioRxiv2019

Genotyping complex structural variation at the malaria-associated human glycophorin locus using a PCR-based strategy

Structural variation in the human genome can affect risk of disease. An example is a complex structural variant of the human glycophorin gene cluster, called DUP4, which is associated with a clinically-significant level of protection against severe malaria. The human glycophorin gene cluster harbours at least 23 distinct structural variants and accurate genotyping of this complex structural variation remains a challenge. Here, we use a PCR-based strategy to genotype structural variation at the human glycophorin gene cluster. We validate our approach, based on a triplex paralogue ratio test (PRT) combined with junction-fragment specific PCR, on publically-available samples from the 1000 Genomes project. We then genotype a longitudinal birth cohort using small amounts of DNA at low cost. Our approach readily identifies known deletions and duplications, and can potentially identify novel variants for further analysis. It will allow exploration of genetic variation at the glycophorin locus, and investigation of its relationship with malaria, in large sample sets at minimal cost, using standard molecular biology equipment.

genetics↗

bioRxiv2019

Linked optical and gene expression profiling of single cells at high throughput

Single cell RNA sequencing has emerged as a powerful tool for characterizing cells, but not all phenotypes of interest can be observed through gene expression alone. Linking sequencing with optical analysis has provided insight into the molecular basis behind cellular function, but current approaches have limited throughput. Here, we present a high throughput platform for linked optical and gene expression profiling of single cells. We demonstrate accurate fluorescence and gene expression measurements from thousands of cells in a single experiment and use the platform to characterize DNA and RNA changes in Jurkat cells through the cell cycle. In addition to its scalability, our integration of microfluidics and array-based molecular biology holds promise for comprehensive multi-omics profiling of single cells.

bioengineering↗

bioRxiv2019

Gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure

Understanding the genetic regulatory code that governs gene expression is a primary, yet challenging aspiration in molecular biology that opens up possibilities to cure human diseases and solve biotechnology problems. However, the fundamental question of how each of the individual coding and non-coding regions of the gene regulatory structure interact and contribute to the mRNA expression levels remains unanswered. Considering that all the information for gene expression regulation is already present in living cells, here we applied deep learning on over 20,000 mRNA datasets in 7 model organisms ranging from bacteria to Human. We show that in all organisms, mRNA abundance can be predicted directly from the DNA sequence with high accuracy, demonstrating that up to 82% of the variation of gene expression levels is encoded in the gene regulatory structure. Coding and non-coding regions carry both overlapping and orthogonal information and additively contribute to gene expression levels. By searching for DNA regulatory motifs present across the whole gene regulatory structure, we discover that motif interactions can regulate gene expression levels in a range of over three orders of magnitude. The uncovered co-evolution of coding and non-coding regions challenges the current paradigm that single motifs or regions are solely responsible for gene expression levels. Instead, we show that the correct combination of all regulatory regions must be established in order to accurately control gene expression levels. Therefore, the holistic system that spans the entire gene regulatory structure is required to analyse, understand, and design any future gene expression systems.

systems biology↗

bioRxiv2019

eMED-DNA: An in silico operating system for clinical medical data storage within the human genome

The propitious developments in molecular biology and next generation sequencing have enabled the possibility for DNA storage technologies. However, the full application and power of our genomic revolution have not been fully utilized in clinical medicine given a lack of transition from research to real world clinical practice. This has identified an increasing need for an operating system which allows for the transition from research to clinical use. We present eMED-DNA, an in silico operating system for archiving and managing all forms of electronic health records (EHRs) within ones own copy of the sequenced genome to aid in the application and integration of genomic medicine within real world clinical practice. We incorporated an efficient and sophisticated in-DNA file management system for the lossless management of EHRs within a genome. This represents the first in silico integrative system which would bring closer the utopian ideal for integrating genotypic data with phenotypic clinical data for future medical practice.

bioinformatics↗

bioRxiv2019

Cross-kingdom regulation of tRNAs/tRFs derived from Chinese yew

Plants containing countless chemical constituent have benefited mankind since the origin of life. Although secondary metabolites in plants, such as morphine, artemisinin and taxol, have been developed as therapeutic drugs for clinical therapy, few study focuses on the pharmacological activities of plant small RNAs with function of cross-kingdom regulations. Yew is widely considered as a \"superstar\" plant due to the discovery of paclitaxel, or taxol, which is a well-known natural drug for the treatment of multiple types of cancer1. Here we show the surprising finding that an RNA fragment, named tRF-T11, derived from tRNAHis(GUG) of Chinese yew strongly suppressed human ovarian cancer progression. In A2780 cells, tRF-T11 mimic (a double-stranded RNA with tRF-T11 as antisense chain) exhibited potent cytotoxicity comparable to that of taxol, but no significant cytotoxicity to normal ovarian surface epithelial cells. Moreover, the cytotoxicity of tRF-T11 mimic is 80-fold stronger than that of taxol in taxol-resistant A2780 cells. Bioinformatic and molecular biological studies revealed that tRF-T11 targets transient receptor potential cation channel subfamily A member 1 (TRPA1) to inhibit its expression levels. In a further in vivo investigation, the growth rate of ovarian tumor xenografts in nude mice was significantly reduced by treatment with tRF-T11 mimic, and the TRPA1 protein expression in tumors treated with tRF-T11 mimic was also down-regulated. Our findings are the first to provide evidence that plant-derived tRFs can regulate the expression of target genes in vitro and in vivo, indicating that they may become as a new source of druggable siRNA. Moreover, this discovery demonstrated a pilot example of an innovative approach for not only identifying pharmacologically-active tRFs from plants, but also for improving the efficiency and possibilities of discovering new drug target.

cell biology↗

bioRxiv2019

Isolation and molecular identification of pectinase producing Aspergillus species from different soil samples of Bhubaneswar regions

With the significant improvement of human civilization there is a spur in the urban, rural and industrial development, which has a profound effect on the surrounding natural environment. Increased utilization of natural resources is often associated with accumulation of waste materials whose management is crucial for sustainable development of life. Availability of different microorganisms in the soil facilitates the degradation of wastes through their potential enzymatic activities. Pectinase seems to be one of the important enzymes produced by a wide variety of microorganisms contained in the soil. It is mainly involved in maceration and rotting of plant extracts and debris by hydrolysis of 1,4-alpha glycosidic bonds of de-esterified pectate of plant call wall. In this paper we report molecular identification of some pectinase producing Aspergillus species selected from soil samples of five different zones of Bhubaneswar city using molecular biology and computational techniques. Among fifteen fungal isolates studied from these five zones Aspergillus parvisclerotigenus was potent for pectinase production next to Aspergillus niger in form of halozone of 0.6 mm. Its 28S rDNA sequence also had some significant identity (>90%) with different subspecies of Aspergillus. We hope that our findings will helpful in genetic manipulation for improvement of fungal strains of isolates. Again large scale use of the improved Aspergillus strains can degrade plant biomass & diverse industrial wastes which will reduce environmental pollution of capital urban like Bhubaneswar.

microbiology↗

bioRxiv2019

Multiplexed direct detection of barcoded protein reporters on a nanopore array

Genetically encoded reporter proteins are a cornerstone of molecular biology. While they are widely used to measure many biological activities, the current number of uniquely addressable reporters that can be used together for one-pot multiplexed tracking is small due to overlapping detection channels such as fluorescence. To address this, we built an expanded library of orthogonally-barcoded Nanopore-addressable protein Tags Engineered as Reporters (NanoporeTERs), which can be read and demuxed by nanopore sensors at the single-molecule level. By adapting a commercially available nanopore sensor array platform typically used for real-time DNA and RNA sequencing (Oxford Nanopore Technologies MinION), we show direct detection of NanoporeTER expression levels from unprocessed bacterial culture with no specialized sample preparation. These results lay the foundations for a new class of reporter proteins to enable multiplexed, real-time tracking of gene expression with nascent nanopore sensor technology.

synthetic biology↗