Editorial: NAR surveys the past, present and future of restriction endonucleases

Development and validation of AI/ML derived splice-switching oligonucleotides

Splice-switching oligonucleotides (SSOs) are antisense compounds that act directly on pre-mRNA to modulate alternative splicing (AS). This study demonstrates the value that artificial intelligence/machine learning (AI/ML) provides for the identification of functional, verifiable, and therapeutic SSOs. We trained XGboost tree models using splicing factor (SF) pre-mRNA binding profiles and spliceosome assembly information to identify modulatory SSO binding sites on pre-mRNA. Using Shapley and out-of-bag analyses we also predicted the identity of specific SFs whose binding to pre-mRNA is blocked by SSOs. This step adds considerable transparency to AI/ML-driven drug discovery and informs biological insights useful in further validation steps. We applied this approach to previously established functional SSOs to retrospectively identify the SFs likely to regulate those events. We then took a prospective validation approach using a novel target in triple negative breast cancer (TNBC), NEDD4L exon 13 (NEDD4Le13). Targeting NEDD4Le13 with an AI/ML-designed SSO decreased the proliferative and migratory behavior of TNBC cells via downregulation of the TGFβ pathway. Overall, this study illustrates the ability of AI/ML to extract actionable insights from RNA-seq data.

Effect of Selective Lesions of Nucleus Accumbens µ-Opioid Receptor-Expressing Cells on Heroin Self-Administration in Male and Female Rats: A Study with Novel Oprm1-Cre Knock-in Rats

The brain µ-opioid receptor (MOR) is critical for the analgesic, rewarding, and addictive effects of opioid drugs. However, in rat models of opioid-related behaviors, the circuit mechanisms of MOR-expressing cells are less known because of a lack of genetic tools to selectively manipulate them. We introduce a CRISPR-based Oprm1-Cre knock-in transgenic rat that provides cell type-specific genetic access to MOR-expressing cells. After performing anatomic and behavioral validation experiments, we used the Oprm1-Cre knock-in rats to study the involvement of NAc MOR-expressing cells in heroin self-administration in male and female rats. Using RNAscope, autoradiography, and FISH chain reaction (HCR-FISH), we found no differences in Oprm1 expression in NAc, dorsal striatum, and dorsal hippocampus, or MOR receptor density (except dorsal striatum) or function between Oprm1-Cre knock-in rats and wildtype littermates. HCR-FISH assay showed that iCre is highly coexpressed with Oprm1 (95%-98%). There were no genotype differences in pain responses, morphine analgesia and tolerance, heroin self-administration, and relapse-related behaviors. We used the Cre-dependent vector AAV1-EF1a-Flex-taCasp3-TEVP to lesion NAc MOR-expressing cells. We found that the lesions decreased acquisition of heroin self-administration in male Oprm1-Cre rats and had a stronger inhibitory effect on the effort to self-administer heroin in female Oprm1-Cre rats. The validation of an Oprm1-Cre knock-in rat enables new strategies for understanding the role of MOR-expressing cells in rat models of opioid addiction, pain-related behaviors, and other opioid-mediated functions. Our initial mechanistic study indicates that lesioning NAc MOR-expressing cells had different effects on heroin self-administration in male and female rats.SIGNIFICANCE STATEMENT The brain µ-opioid receptor (MOR) is critical for the analgesic, rewarding, and addictive effects of opioid drugs. However, in rat models of opioid-related behaviors, the circuit mechanisms of MOR-expressing cells are less known because of a lack of genetic tools to selectively manipulate them. We introduce a CRISPR-based Oprm1-Cre knock-in transgenic rat that provides cell type-specific genetic access to brain MOR-expressing cells. After performing anatomical and behavioral validation experiments, we used the Oprm1-Cre knock-in rats to show that lesioning NAc MOR-expressing cells had different effects on heroin self-administration in males and females. The new Oprm1-Cre rats can be used to study the role of brain MOR-expressing cells in animal models of opioid addiction, pain-related behaviors, and other opioid-mediated functions.

MiR-21 regulating PVT1/PTEN/IL-17 axis towards the treatment of infectious diabetic wound healing by modified GO-derived biomaterial in mouse models

BACKGROUND

Diabetic foot ulcer (DFU), persistent hyperglycemia and inflammation, together with impaired nutrient and oxygen deficiency, can present abnormal angiogenesis following tissue injury such that these tissues fail to heal properly. It is critical to design a new treatment method for DFU patients with a distinct biomechanism that is more effective than current treatment regimens.

METHOD

Graphene oxide (GO) was combined with a biocompatible polymer as a kind of modified GO-based hydrogel. The characterization of our biomaterial was measured in vitro. The repair efficiency of the biomaterial was evaluated in the mouse full-skin defect models. The key axis related to diabetic wound (DW) was identified and investigated using bioinformatics analyses and practical experiments.

RESULT

In the study, we found that our modified GO-based wound dressing material is a promising option for diabetic wound. Secondly, our biomaterial could enhance the secretion of small EVs (sEVs) with more miR-21 by adipose-derived mesenchymal stem cells (AD-MSCs). Thirdly, the PVT1/PTEN/IL-17 axis was found to be decreased to promote DFU wound healing by modifying miR-21 with the discovery of PVT1 as a critical LncRNA by bioinformatics analysis and tests.

CONCLUSION

These findings could aid in the development of clinical care strategies for DFU wounds.

Optimization of the antimicrobial peptide Bac7 by deep mutational scanning

Background

Intracellularly active antimicrobial peptides are promising candidates for the development of antibiotics for human applications. However, drug development using peptides is challenging as, owing to their large size, an enormous sequence space is spanned. We built a high-throughput platform that incorporates rapid investigation of the sequence-activity relationship of peptides and enables rational optimization of their antimicrobial activity. The platform is based on deep mutational scanning of DNA-encoded peptides and employs highly parallelized bacterial self-screening coupled to next-generation sequencing as a readout for their antimicrobial activity. As a target, we used Bac7_1-23, a 23 amino acid residues long variant of bactenecin-7, a potent translational inhibitor and one of the best researched proline-rich antimicrobial peptides.

Results

Using the platform, we simultaneously determined the antimicrobial activity of >600,000 Bac7_1-23 variants and explored their sequence-activity relationship. This dataset guided the design of a focused library of ~160,000 variants and the identification of a lead candidate Bac7PS. Bac7PS showed high activity against multidrug-resistant clinical isolates of E. coli, and its activity was less dependent on SbmA, a transporter commonly used by proline-rich antimicrobial peptides to reach the cytosol and then inhibit translation. Furthermore, Bac7PS displayed strong ribosomal inhibition and low toxicity against eukaryotic cells and demonstrated good efficacy in a murine septicemia model induced by E. coli.

Conclusion

We demonstrated that the presented platform can be used to establish the sequence-activity relationship of antimicrobial peptides, and showed its usefulness for hit-to-lead identification and optimization of antimicrobial drug candidates.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01304-4.

Integrative structure determination reveals functional global flexibility for an ultra-multimodular arabinanase

AbnA is an extracellular GH43 α-L-arabinanase from Geobacillus stearothermophilus, a key bacterial enzyme in the degradation and utilization of arabinan. We present herein its full-length crystal structure, revealing the only ultra-multimodular architecture and the largest structure to be reported so far within the GH43 family. Additionally, the structure of AbnA appears to contain two domains belonging to new uncharacterized carbohydrate-binding module (CBM) families. Three crystallographic conformational states are determined for AbnA, and this conformational flexibility is thoroughly investigated further using the "integrative structure determination" approach, integrating molecular dynamics, metadynamics, normal mode analysis, small angle X-ray scattering, dynamic light scattering, cross-linking, and kinetic experiments to reveal large functional conformational changes for AbnA, involving up to ~100 Å movement in the relative positions of its domains. The integrative structure determination approach demonstrated here may apply also to the conformational study of other ultra-multimodular proteins of diverse functions and structures.

Genome editing in animals with minimal PAM CRISPR-Cas9 enzymes

The requirement for Cas nucleases to recognize a specific PAM is a major restriction for genome editing. SpCas9 variants SpG and SpRY, recognizing NGN and NRN PAMs, respectively, have contributed to increase the number of editable genomic sites in cell cultures and plants. However, their use has not been demonstrated in animals. Here we study the nuclease activity of SpG and SpRY by targeting 40 sites in zebrafish and C. elegans. Delivered as mRNA-gRNA or ribonucleoprotein (RNP) complexes, SpG and SpRY were able to induce mutations in vivo, albeit at a lower rate than SpCas9 in equivalent formulations. This lower activity was overcome by optimizing mRNA-gRNA or RNP concentration, leading to mutagenesis at regions inaccessible to SpCas9. We also found that the CRISPRscan algorithm could help to predict SpG and SpRY targets with high activity in vivo. Finally, we applied SpG and SpRY to generate knock-ins by homology-directed repair. Altogether, our results expand the CRISPR-Cas targeting genomic landscape in animals.

Purification of multiplex oligonucleotide libraries by synthesis and selection

Complex oligonucleotide (oligo) libraries are essential materials for diverse applications in synthetic biology, pharmaceutical production, nanotechnology and DNA-based data storage. However, the error rates in synthesizing complex oligo libraries can be substantial, leading to increment in cost and labor for the applications. As most synthesis errors arise from faulty insertions and deletions, we developed a length-based method with single-base resolution for purification of complex libraries containing oligos of identical or different lengths. Our method-purification of multiplex oligonucleotide libraries by synthesis and selection-can be performed either step-by-step manually or using a next-generation sequencer. When applied to a digital data-encoded library containing oligos of identical length, the method increased the purity of full-length oligos from 83% to 97%. We also show that libraries encoding the complementarity-determining region H3 with three different lengths (with an empirically achieved diversity >10⁶) can be simultaneously purified in one pot, increasing the in-frame oligo fraction from 49.6% to 83.5%.

Comparison of machine learning and deep learning techniques in promoter prediction across diverse species

Gene promoters are the key DNA regulatory elements positioned around the transcription start sites and are responsible for regulating gene transcription process. Various alignment-based, signal-based and content-based approaches are reported for the prediction of promoters. However, since all promoter sequences do not show explicit features, the prediction performance of these techniques is poor. Therefore, many machine learning and deep learning models have been proposed for promoter prediction. In this work, we studied methods for vector encoding and promoter classification using genome sequences of three distinct higher eukaryotes viz. yeast (Saccharomyces cerevisiae), A. thaliana (plant) and human (Homo sapiens). We compared one-hot vector encoding method with frequency-based tokenization (FBT) for data pre-processing on 1-D Convolutional Neural Network (CNN) model. We found that FBT gives a shorter input dimension reducing the training time without affecting the sensitivity and specificity of classification. We employed the deep learning techniques, mainly CNN and recurrent neural network with Long Short Term Memory (LSTM) and random forest (RF) classifier for promoter classification at k-mer sizes of 2, 4 and 8. We found CNN to be superior in classification of promoters from non-promoter sequences (binary classification) as well as species-specific classification of promoter sequences (multiclass classification). In summary, the contribution of this work lies in the use of synthetic shuffled negative dataset and frequency-based tokenization for pre-processing. This study provides a comprehensive and generic framework for classification tasks in genomic applications and can be extended to various classification problems.

Culicidae evolutionary history focusing on the Culicinae subfamily based on mitochondrial phylogenomics

Mosquitoes are insects of medical importance due their role as vectors of different pathogens to humans. There is a lack of information about the evolutionary history and phylogenetic positioning of the majority of mosquito species. Here we characterized the mitogenomes of mosquito species through low-coverage whole genome sequencing and data mining. A total of 37 draft mitogenomes of different species were assembled from which 16 are newly-sequenced species. We datamined additional 49 mosquito mitogenomes, and together with our 37 mitogenomes, we reconstructed the evolutionary history of 86 species including representatives from 15 genera and 7 tribes. Our results showed that most of the species clustered in clades with other members of their own genus with exception of Aedes genus which was paraphyletic. We confirmed the monophyletic status of the Mansoniini tribe including both Coquillettidia and Mansonia genus. The Aedeomyiini and Uranotaeniini were consistently recovered as basal to other tribes in the subfamily Culicinae, although the exact relationships among these tribes differed between analyses. These results demonstrate that low-coverage sequencing is effective to recover mitogenomes, establish phylogenetic knowledge and hence generate basic fundamental information that will help in the understanding of the role of these species as pathogen vectors.

Ancestral function of Inhibitors-of-kappaB regulates Caenorhabditis elegans development

Mammalian IκB proteins (IκBs) exert their main function as negative regulators of NF-κB, a central signaling pathway controlling immunity and inflammation. An alternative chromatin role for IκBs has been shown to affect stemness and cell differentiation. However, the involvement of NF-κB in this function has not been excluded. NFKI-1 and IKB-1 are IκB homologs in Caenorhabditis elegans, which lacks NF-κB nuclear effectors. We found that nfki-1 and ikb-1 mutants display developmental defects that phenocopy mutations in Polycomb and UTX-1 histone demethylase, suggesting a role for C. elegans IκBs in chromatin regulation. Further supporting this possibility (1) we detected NFKI-1 in the nucleus of cells; (2) NFKI-1 and IKB-1 bind to histones and Polycomb proteins, (3) and associate with chromatin in vivo, and (4) mutations in nfki-1 and ikb-1 alter chromatin marks. Based on these results, we propose that ancestral IκB inhibitors modulate Polycomb activity at specific gene subsets with an impact on development.

Conditionally essential genes for survival during starvation in Enterococcus faecium E745

BACKGROUND

The nosocomial pathogen Enterococcus faecium can survive for prolonged periods of time on surfaces in the absence of nutrients. This trait is thought to contribute to the ability of E. faecium to spread among patients in hospitals. There is currently a lack of data on the mechanisms that are responsible for the ability of E. faecium to survive in the absence of nutrients.

RESULTS

We performed a high-throughput transposon mutant library screening (Tn-seq) to identify genes that have a role in long-term survival during incubation in phosphate-buffered saline (PBS) at 20 °C. A total of 24 genes were identified by Tn-seq to contribute to survival in PBS, with functions associated with the general stress response, DNA repair, metabolism, and membrane homeostasis. The gene which was quantitatively most important for survival in PBS was usp (locus tag: EfmE745_02439), which is predicted to encode a 17.4 kDa universal stress protein. After generating a targeted deletion mutant in usp, we were able to confirm that usp significantly contributes to survival in PBS and this defect was restored by in trans complementation. The usp gene is present in 99% of a set of 1644 E. faecium genomes that collectively span the diversity of the species.

CONCLUSIONS

We postulate that usp is a key determinant for the remarkable environmental robustness of E. faecium. Further mechanistic studies into usp and other genes identified in this study may shed further light on the mechanisms by which E. faecium can survive in the absence of nutrients for prolonged periods of time.

Exploring the diversity of Poaceae-infecting mastreviruses on Reunion Island using a viral metagenomics-based approach

Mostly found in Africa and its surrounding islands, African streak viruses (AfSV) represent the largest group of known mastreviruses. Of the thirteen AfSV species that are known to infect either cultivated or wild Poaceae plant species, six have been identified on Reunion Island. To better characterize AfSV diversity on this island, we undertook a survey of a small agroecosystem using a new metagenomics-based approach involving rolling circle amplification with random PCR amplification tagging (RCA-RA-PCR), high-throughput sequencing (Illumina HiSeq) and the mastrevirus reads classification using phylogenetic placement. Mastreviruses that likely belong to three new species were discovered and full genome sequences of these were determined by Sanger sequencing. The geminivirus-focused metagenomics approach we applied in this study was useful in both the detection of known and novel mastreviruses. The results confirm that Reunion Island is indeed a hotspot of AfSV diversity and that many of the mastrevirus species have likely been introduced multiple times. Applying a similar approach in other natural and agricultural environments should yield sufficient detail on the composition and diversity of geminivirus communities to precipitate major advances in our understanding of the ecology and the evolutionary history of this important group of viruses.

Community profiling of the urinary microbiota: considerations for low-biomass samples

Many studies have shown that the urinary tract harbours its own microbial community known as the urinary microbiota, which have been implicated in urinary tract disorders. This observation contradicts the long-held notion that urine is a sterile biofluid in the absence of acute infection of the urinary tract. In light of this new discovery, many basic questions that are crucial for understanding the role of the urinary microbiota in human health and disease remain unanswered. Given that the urinary microbiota is an emerging area of study, optimized techniques and protocols to identify microorganisms in the urinary tract are still being established. However, the low microbial biomass and close proximity to higher microbial biomass environments (for example, the vagina) present distinct methodological challenges for microbial community profiling of the urinary microbiota. A clear understanding of the unique technical considerations for obtaining and analysing low microbial biomass samples, as well the influence of key elements of experimental design and computational analysis on downstream interpretation, will improve our ability to interpret and compare results across methods and studies and is relevant for studies profiling the urinary microbiota and other sites of low microbial abundance.

EXOSC10 is required for RPA assembly and controlled DNA end resection at DNA double-strand breaks

The exosome is a ribonucleolytic complex that plays important roles in RNA metabolism. Here we show that the exosome is necessary for the repair of DNA double-strand breaks (DSBs) in human cells and that RNA clearance is an essential step in homologous recombination. Transcription of DSB-flanking sequences results in the production of damage-induced long non-coding RNAs (dilncRNAs) that engage in DNA-RNA hybrid formation. Depletion of EXOSC10, an exosome catalytic subunit, leads to increased dilncRNA and DNA-RNA hybrid levels. Moreover, the targeting of the ssDNA-binding protein RPA to sites of DNA damage is impaired whereas DNA end resection is hyper-stimulated in EXOSC10-depleted cells. The DNA end resection deregulation is abolished by transcription inhibitors, and RNase H1 overexpression restores the RPA recruitment defect caused by EXOSC10 depletion, which suggests that RNA clearance of newly synthesized dilncRNAs is required for RPA recruitment, controlled DNA end resection and assembly of the homologous recombination machinery.

Network-based approach to identify principal isoforms among four cancer types

Protein isoforms are structurally similar proteins produced by alternative splicing of a single gene or genes from the same family. Isoforms of a protein can perform the same, similar, or even opposite biological functions. A previous study identified principal isoforms of proteins based on the extent of interactions per isoform in a functional relationship network, focusing on data from normal tissues. Additionally, the expression levels of specific isoforms of various genes associated with tumorigenesis and prognosis are frequently altered in tumors compared with those in normal tissues. In this study, we aimed to identify higher degree isoforms (HDIs) of multi-isoform genes (MIGs) in cancer by applying a meta-analytical framework to calculate co-expression between each pair of isoforms in two large datasets of RNA-seq profiles from breast cancer, lung cancer, leukemia, and colon cancer cell lines. Then, we compared HDIs with isoforms identified by proteomic data and prognostic and predictive evidence in various cancers. In addition, we separately analyzed the associations between HDIs and non-HDIs (nHDIs) of the same genes according to transcript expression and drug responses in various cancer type cell lines. Collectively, these results indicated the complex properties of HDIs per gene identified by cancer type-based isoform-isoform co-expression networks and showed the potential of HDIs as novel therapeutic targets for cancer treatment.

Transcriptional repression by FACT is linked to regulation of chromatin accessibility at the promoter of ES cells

Depletion of FACT in murine embryonic stem cells show mild changes on the nucleosomal landscape but widespread changes in the transcriptome, faster proliferation, and neuronal differentiation rates.

The conserved and essential histone chaperone, facilitates chromatin transcription (FACT), reorganizes nucleosomes during DNA transcription, replication, and repair and ensures both efficient elongation of RNA Pol II and nucleosome integrity. In mammalian cells, FACT is a heterodimer, consisting of SSRP1 and SUPT16. Here, we show that in contrast to yeast, FACT accumulates at the transcription start site of genes reminiscent of RNA polymerase II profile. Depletion of FACT in mouse embryonic stem cells leads to deregulation of developmental and pro-proliferative genes concomitant with hyper-proliferation of mES cells. Using MNase-seq, Assay for Transposase-Accessible Chromatin sequencing, and nascent elongating transcript sequencing, we show that up-regulation of genes coincides with loss of nucleosomes upstream of the transcription start site and concomitant increase in antisense transcription, indicating that FACT impacts the promoter architecture to regulate the expression of these genes. Finally, we demonstrate a role for FACT in cell fate determination and show that FACT depletion primes embryonic stem cells for the neuronal lineage.

Strain-resolved analysis of hospital rooms and infants reveals overlap between the human and room microbiome

Preterm infants exhibit different microbiome colonization patterns relative to full-term infants, and it is speculated that the hospital room environment may contribute to infant microbiome development. Here, we present a genome-resolved metagenomic study of microbial genotypes from the gastrointestinal tracts of infants and from the neonatal intensive care unit (NICU) room environment. Some strains detected in hospitalized infants also occur in sinks and on surfaces, and belong to species such as Staphylococcus epidermidis, Enterococcus faecalis, Pseudomonas aeruginosa, and Klebsiella pneumoniae, which are frequently implicated in nosocomial infection and preterm infant gut colonization. Of the 15 K. pneumoniae strains detected in the study, four were detected in both infant gut and room samples. Time series experiments showed that nearly all strains associated with infant gut colonization can be detected in the room after, and often before, detection in the gut. Thus, we conclude that a component of premature infant gut colonization is the cycle of microbial exchange between the room and the occupant.

It is thought that the hospital environment may contribute to infant microbiome development. Here, Brooks et al. present a genome-resolved metagenomic study of microbial genotypes from the infant gut and from neonatal intensive care unit rooms, showing that some strains are found in both infants and rooms.

An Assessment of Fixed and Native Chromatin Preparation Methods to Study Histone Post-Translational Modifications at a Whole Genome Scale in Skeletal Muscle Tissue

Background

Genomic loci associated with histone marks are typically analyzed by immunoprecipitation of the chromatin followed by quantitative-PCR (ChIP-qPCR) or high throughput sequencing (ChIP-seq). Chromatin can be either cross-linked (X-ChIP) or used in the native state (N-ChIP). Cross-linking of DNA and proteins helps stabilizing their interactions before analysis. Despite X-ChIP is the most commonly used method, muscle tissue fixation is known to be relatively inefficient. Moreover, no protocol described a simple and reliable preparation of skeletal muscle chromatin of sufficient quality for subsequent high-throughput sequencing. Here we aimed to set-up and compare both chromatin preparation methods for a genome-wide analysis of H3K27me3, a broad-peak histone mark, using chicken P. major muscle tissue.

Results

Fixed and unfixed chromatin were prepared from chicken muscle tissues (Pectoralis major). Chromatin fixation, shearing by sonication or digestion and immunoprecipitation performed equivalently. High-quality Illumina reads were obtained (q30 > 93%). The bioinformatic analysis of the data was performed using epic, a tool based on SICER, and MACS2. Forty millions of reads were analyzed for both X-ChIP-seq and N-ChIP-seq experiments. Surprisingly, H3K27me3 X-ChIP-seq analysis led to the identification of only 2000 enriched regions compared to about 15,000 regions identified in the case of N-ChIP-seq. N-ChIP-seq peaks were more consistent between replicates compared to X-ChIP-seq. Higher N-ChIP-seq enrichments were confirmed by ChIP-qPCR at the PAX5 and SOX2 loci known to be enriched for H3K27me3 in myotubes and at the loci of common regions of enrichment identified in this study.

Conclusions

Our findings suggest that the preparation of muscle chromatin for ChIP-seq in cross-linked conditions can compromise the systematic analysis of broad histone marks. Therefore, native chromatin preparation should be preferred to cross-linking when a ChIP experiment has to be performed on skeletal muscle tissue, particularly when a broad source signal is considered.

Electronic supplementary material

The online version of this article (doi:10.1186/s12575-017-0059-0) contains supplementary material, which is available to authorized users.

Time-Sampled Population Sequencing Reveals the Interplay of Selection and Genetic Drift in Experimental Evolution of Potato Virus Y

RNA viruses are one of the fastest-evolving biological entities. Within their hosts, they exist as genetically diverse populations (i.e., viral mutant swarms), which are sculpted by different evolutionary mechanisms, such as mutation, natural selection, and genetic drift, and also the interactions between genetic variants within the mutant swarms. To elucidate the mechanisms that modulate the population diversity of an important plant-pathogenic virus, we performed evolution experiments with Potato virus Y (PVY) in potato genotypes that differ in their defense response against the virus. Using deep sequencing of small RNAs, we followed the temporal dynamics of standing and newly generated variations in the evolving viral lineages. A time-sampled approach allowed us to (i) reconstruct theoretical haplotypes in the starting population by using clustering of single nucleotide polymorphisms' trajectories and (ii) use quantitative population genetics approaches to estimate the contribution of selection and genetic drift, and their interplay, to the evolution of the virus. We detected imprints of strong selective sweeps and narrow genetic bottlenecks, followed by the shift in frequency of selected haplotypes. Comparison of patterns of viral evolution in differently susceptible host genotypes indicated possible diversifying evolution of PVY in the less-susceptible host (efficient in the accumulation of salicylic acid).IMPORTANCE High diversity of within-host populations of RNA viruses is an important aspect of their biology, since they represent a reservoir of genetic variants, which can enable quick adaptation of viruses to a changing environment. This study focuses on an important plant virus, Potato virus Y, and describes, at high resolution, temporal changes in the structure of viral populations within different potato genotypes. A novel and easy-to-implement computational approach was established to cluster single nucleotide polymorphisms into viral haplotypes from very short sequencing reads. During the experiment, a shift in the frequency of selected viral haplotypes was observed after a narrow genetic bottleneck, indicating an important role of the genetic drift in the evolution of the virus. On the other hand, a possible case of diversifying selection of the virus was observed in less susceptible host genotypes.

Visualizing single-stranded nucleic acids in solution

Single-stranded nucleic acids (ssNAs) are ubiquitous in many key cellular functions. Their flexibility limits both the number of high-resolution structures available, leaving only a small number of protein-ssNA crystal structures, while forcing solution investigations to report ensemble averages. A description of the conformational distributions of ssNAs is essential to more fully characterize biologically relevant interactions. We combine small angle X-ray scattering (SAXS) with ensemble-optimization methods (EOM) to dynamically build and refine sets of ssNA structures. By constructing candidate chains in representative dinucleotide steps and refining the models against SAXS data, a broad array of structures can be obtained to match varying solution conditions and strand sequences. In addition to the distribution of large scale structural parameters, this approach reveals, for the first time, intricate details of the phosphate backbone and underlying strand conformations. Such information on unperturbed strands will critically inform a detailed understanding of an array of problems including protein-ssNA binding, RNA folding and the polymer nature of NAs. In addition, this scheme, which couples EOM selection with an iteratively refining pool to give confidence in the underlying structures, is likely extendable to the study of other flexible systems.

Modeling protein-DNA binding via high-throughput in vitro technologies

Protein-DNA binding plays a central role in gene regulation and by that in all processes in the living cell. Novel experimental and computational approaches facilitate better understanding of protein-DNA binding preferences via high-throughput measurement of protein binding to a large number of DNA sequences and inference of binding models from them. Here we review the state of the art in measuring protein-DNA binding in vitro, emphasizing the advantages and limitations of different technologies. In addition, we describe models for representing protein-DNA binding preferences and key computational approaches to learn those from high-throughput data. Using large experimental data sets, we test the performance of different models based on different measuring techniques. We conclude with pertinent open problems.

Deep sequencing of phage-displayed peptide libraries reveals sequence motif that detects norovirus

Norovirus infections are the leading cause of non-bacterial gastroenteritis and result in about 21 million new cases and $2 billion in costs per year in the United States. Existing diagnostics have limited feasibility for point-of-care applications, so there is a clear need for more reliable, rapid, and simple-to-use diagnostic tools in order to contain outbreaks and prevent inappropriate treatments. In this study, a combination of phage display technology, deep sequencing and computational analysis was used to identify 12-mer peptides with specific binding to norovirus genotype GI.1 virus-like particles (VLPs). After biopanning, phage populations were sequenced and analyzed to identify a consensus peptide motif-YRSWXP. Two 12-mer peptides containing this sequence, NV-O-R5-3 and NV-O-R5-6, were further characterized to evaluate the motif's functional ability to detect VLPs and virus. Results indicated that these peptides effectively detect GI.1 VLPs in solid-phase peptide arrays, ELISAs and dot blots. Further, their specificity for the S-domain of the major capsid protein enables them to detect a wide range of GI and GII norovirus genotypes. Both peptides were able to detect virus in norovirus-positive clinical stool samples. Overall, the work reported here demonstrates the application of phage display coupled with next generation sequencing and computational analysis to uncover peptides with specific binding ability to a target protein for diagnostic applications. Further, the reagents characterized here can be integrated into existing diagnostic formats to detect clinically relevant genotypes of norovirus in stool.

Exposing the Molecular Screening Method of Indonesian Natural Products Derivate as Drug Candidates for Cervical Cancer

The menace of cervical cancer has reached an alarming rate. There are more than 450.000 cases of cervical cancer yearly, with mortality rate of about 50%. This deadly cancer is caused by human papillomavirus (HPV), mainly subtypes 16 and 18. The pharmaceutical industry has produced drug for combating the virus, known as SAHA (suberoylanilide hydroxamic acid). It inhibits class II HDAC Homo sapiens (HDACi). The utilization of SAHA has some side effects, one of which is bone loss. Thus, searching for viable alternatives aside SAHA is inevitable. The objective of this research is to investigate the molecular interaction of selected Indonesian natural products with class II HDAC Homo sapiens. LigX tool in MOE 2008.10 was used as an instrument to investigate the molecular interaction. Then, computer-aided drug discovery and development (CADDD) approach involving molecular docking and dynamics methods was utilized to screen the natural products library. In the end, we found that herbaric acid could act as a potential drug candidate for cervical cancer.

An efficient system for selectively altering genetic information within mRNAs

Site-directed RNA editing (SDRE) is a strategy to precisely alter genetic information within mRNAs. By linking the catalytic domain of the RNA editing enzyme ADAR to an antisense guide RNA, specific adenosines can be converted to inosines, biological mimics for guanosine. Previously, we showed that a genetically encoded iteration of SDRE could target adenosines expressed in human cells, but not efficiently. Here we developed a reporter assay to quantify editing, and used it to improve our strategy. By enhancing the linkage between ADAR's catalytic domain and the guide RNA, and by introducing a mutation in the catalytic domain, the efficiency of converting a U A: G premature termination codon (PTC) to tryptophan (U G: G) was improved from ∼11 % to ∼70 %. Other PTCs were edited, but less efficiently. Numerous off-target edits were identified in the targeted mRNA, but not in randomly selected endogenous messages. Off-target edits could be eliminated by reducing the amount of guide RNA with a reduction in on-target editing. The catalytic rate of SDRE was compared with those for human ADARs on various substrates and found to be within an order of magnitude of most. These data underscore the promise of site-directed RNA editing as a therapeutic or experimental tool.

Protein-RNA interactions: structural biology and computational modeling techniques

RNA-binding proteins are functionally diverse within cells, being involved in RNA-metabolism, translation, DNA damage repair, and gene regulation at both the transcriptional and post-transcriptional levels. Much has been learnt about their interactions with RNAs through structure determination techniques and computational modeling. This review gives an overview of the structural data currently available for protein-RNA complexes, and discusses the technical issues facing structural biologists working to solve their structures. The review focuses on three techniques used to solve the 3-dimensional structure of protein-RNA complexes at atomic resolution, namely X-ray crystallography, solution nuclear magnetic resonance (NMR) and cryo-electron microscopy (cryo-EM). The review then focuses on the main computational modeling techniques that use these atomic resolution data: discussing the prediction of RNA-binding sites on unbound proteins, docking proteins, and RNAs, and modeling the molecular dynamics of the systems. In conclusion, the review looks at the future directions this field of research might take.

RStrucFam: a web server to associate structure and cognate RNA for RNA-binding proteins from sequence information

Background

RNA-binding proteins (RBPs) interact with their cognate RNA(s) to form large biomolecular assemblies. They are versatile in their functionality and are involved in a myriad of processes inside the cell. RBPs with similar structural features and common biological functions are grouped together into families and superfamilies. It will be useful to obtain an early understanding and association of RNA-binding property of sequences of gene products. Here, we report a web server, RStrucFam, to predict the structure, type of cognate RNA(s) and function(s) of proteins, where possible, from mere sequence information.

Results

The web server employs Hidden Markov Model scan (hmmscan) to enable association to a back-end database of structural and sequence families. The database (HMMRBP) comprises of 437 HMMs of RBP families of known structure that have been generated using structure-based sequence alignments and 746 sequence-centric RBP family HMMs. The input protein sequence is associated with structural or sequence domain families, if structure or sequence signatures exist. In case of association of the protein with a family of known structures, output features like, multiple structure-based sequence alignment (MSSA) of the query with all others members of that family is provided. Further, cognate RNA partner(s) for that protein, Gene Ontology (GO) annotations, if any and a homology model of the protein can be obtained. The users can also browse through the database for details pertaining to each family, protein or RNA and their related information based on keyword search or RNA motif search.

Conclusions

RStrucFam is a web server that exploits structurally conserved features of RBPs, derived from known family members and imprinted in mathematical profiles, to predict putative RBPs from sequence information. Proteins that fail to associate with such structure-centric families are further queried against the sequence-centric RBP family HMMs in the HMMRBP database. Further, all other essential information pertaining to an RBP, like overall function annotations, are provided. The web server can be accessed at the following link: http://caps.ncbs.res.in/rstrucfam.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1289-x) contains supplementary material, which is available to authorized users.

The Stepwise Increase in the Number of Transcription Factor Families in the Precambrian Predated the Diversification of Plants On Land

The colonization of the land by streptophytes and their subsequent radiation is a major event in Earth history. We report a stepwise increase in the number of transcription factor (TF) families and subfamilies in Archaeplastida before the colonization of the land. The subsequent increase in TF number on land was through duplication within existing TF families and subfamilies. Almost all subfamilies of the Homeodomain (HD) and basic Helix-Loop-Helix (bHLH) had evolved before the radiation of extant land plant lineages from a common ancestor. We demonstrate that the evolution of these TF families independently followed similar trends in both plants and metazoans; almost all extant HD and bHLH subfamilies were present in the first land plants and in the last common ancestor of bilaterians. These findings reveal that the majority of innovation in plant and metazoan TF families occurred in the Precambrian before the Phanerozoic radiation of land plants and metazoans.

Integrating, summarizing and visualizing GWAS-hits and human diversity with DANCE (Disease-ANCEstry networks)

MOTIVATION

The 1000 Genomes Project (1KGP) and thousands of Genome-Wide Association Studies (GWAS) performed during the last years have generated an enormous amount of information that needs to be integrated to better understand the genetic architecture of complex diseases in different populations. This integration is important in areas such as genetics, epidemiology, anthropology, as well as admixture mapping design and GWAS-replications. Network-based approaches that explore the genetic bases of human diseases and traits have not yet incorporated information on genetic diversity among human populations.

RESULTS

We propose Disease-ANCEstry networks (DANCE), a graph-based web tool that allows to integrate and visualize information on human complex phenotypes and their GWAS-hits, as well as their risk allele frequencies in different populations. DANCE provides an interactive way to explore the human SNP-Disease Network and its projection, a Disease-Disease Network. With these functionalities, DANCE fills a gap in our ability to handle and understand the knowledge generated by GWAS and 1KGP. We provide a number of case studies that show how DANCE can be used to explore the relationships between human complex diseases, their genetic bases and variability in different human populations.

AVAILABILITY AND IMPLEMENTATION

DANCE is freely available at http://ldgh.com.br/dance/ We recommend using DANCE with Mozilla Firefox, Safari, Chrome or Internet Explorer (v9 or v10).

CONTACT

gilderlanio@gmail.com or maira.r.rodrigues@gmail.com

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Global analyses of endonucleolytic cleavage in mammals reveal expanded repertoires of cleavage-inducing small RNAs and their targets

In mammals, small RNAs are important players in post-transcriptional gene regulation. While their roles in mRNA destabilization and translational repression are well appreciated, their involvement in endonucleolytic cleavage of target RNAs is poorly understood. Very few microRNAs are known to guide RNA cleavage. Endogenous small interfering RNAs are expected to induce target cleavage, but their target genes remain largely unknown. We report a systematic study of small RNA-mediated endonucleolytic cleavage in mouse through integrative analysis of small RNA and degradome sequencing data without imposing any bias toward known small RNAs. Hundreds of small cleavage-inducing RNAs and their cognate target genes were identified, significantly expanding the repertoire of known small RNA-guided cleavage events. Strikingly, both small RNAs and their target sites demonstrated significant overlap with retrotransposons, providing evidence for the long-standing speculation that retrotransposable elements in mRNAs are leveraged as signals for gene targeting. Furthermore, our analysis showed that the RNA cleavage pathway is also present in human cells but affecting a different repertoire of retrotransposons. These results show that small RNA-guided cleavage is more widespread than previously appreciated. Their impact on retrotransposons in non-coding regions shed light on important aspects of mammalian gene regulation.

Duplication and Diversification of Dipteran Argonaute Genes, and the Evolutionary Divergence of Piwi and Aubergine

Genetic studies of Drosophila melanogaster have provided a paradigm for RNA interference (RNAi) in arthropods, in which the microRNA and antiviral pathways are each mediated by a single Argonaute (Ago1 and Ago2) and germline suppression of transposable elements is mediated by a trio of Piwi-subfamily Argonaute proteins (Ago3, Aub, and Piwi). Without a suitable evolutionary context, deviations from this can be interpreted as derived or idiosyncratic. Here we analyze the evolution of Argonaute genes across the genomes and transcriptomes of 86 Dipteran species, showing that variation in copy number can occur rapidly, and that there is constant flux in some RNAi mechanisms. The lability of the RNAi pathways is illustrated by the divergence of Aub and Piwi (182-156 Ma), independent origins of multiple Piwi-family genes in Aedes mosquitoes (less than 25Ma), and the recent duplications of Ago2 and Ago3 in the tsetse fly Glossina morsitans. In each case the tissue specificity of these genes has altered, suggesting functional divergence or innovation, and consistent with the action of dynamic selection pressures across the Argonaute gene family. We find there are large differences in evolutionary rates and gene turnover between pathways, and that paralogs of Ago2, Ago3, and Piwi/Aub show contrasting rates of evolution after duplication. This suggests that Argonautes undergo frequent evolutionary expansions that facilitate functional divergence.

A Versatile Procedure to Generate Genome-Wide Spatiotemporal Program of Replication in Yeast Species

Here, we describe a complete protocol, comprising both the experimental and the analytical procedures, that allows to generate genome-wide spatiotemporal program of replication and to find the location of chromosomally active replication origins in yeast. The first step consists on synchronizing a cell population by physical discrimination of G1 cells according to their sedimentation coefficient. G1 cells are then synchronously released into S-phase and time-point samples are regularly taken until they reach the G2 phase. Progression through the cell cycle is monitored by measuring DNA content variation by flow cytometry. DNA samples, covering the entire S-phase, are then extracted and analyzed using deep sequencing. The gradual change of DNA copy number is measured to determine the mean replication time along the genome. A simple method of peak calling allows to infer from the replication profile the location of replication origins along the chromosomes. Our protocol is versatile enough to be applied to virtually any yeast species of interest and generate its replication profile.

MMB-GUI: a fast morphing method demonstrates a possible ribosomal tRNA translocation trajectory

Easy-to-use macromolecular viewers, such as UCSF Chimera, are a standard tool in structural biology. They allow rendering and performing geometric operations on large complexes, such as viruses and ribosomes. Dynamical simulation codes enable modeling of conformational changes, but may require considerable time and many CPUs. There is an unmet demand from structural and molecular biologists for software in the middle ground, which would allow visualization combined with quick and interactive modeling of conformational changes, even of large complexes. This motivates MMB-GUI. MMB uses an internal-coordinate, multiscale approach, yielding as much as a 2000-fold speedup over conventional simulation methods. We use Chimera as an interactive graphical interface to control MMB. We show how this can be used for morphing of macromolecules that can be heterogeneous in biopolymer type, sequence, and chain count, accurately recapitulating structural intermediates. We use MMB-GUI to create a possible trajectory of EF-G mediated gate-passing translocation in the ribosome, with all-atom structures. This shows that the GUI makes modeling of large macromolecules accessible to a wide audience. The morph highlights similarities in tRNA conformational changes as tRNA translocates from A to P and from P to E sites and suggests that tRNA flexibility is critical for translocation completion.

Integrated microfluidic approach for quantitative high-throughput measurements of transcription factor binding affinities

Protein binding to DNA is a fundamental process in gene regulation. Methodologies such as ChIP-Seq and mapping of DNase I hypersensitive sites provide global information on this regulation in vivo In vitro methodologies provide valuable complementary information on protein-DNA specificities. However, current methods still do not measure absolute binding affinities. There is a real need for large-scale quantitative protein-DNA affinity measurements. We developed QPID, a microfluidic application for measuring protein-DNA affinities. A single run is equivalent to 4096 gel-shift experiments. Using QPID, we characterized the different affinities of ATF1, c-Jun, c-Fos and AP-1 to the CRE consensus motif and CRE half-site in two different genomic sequences on a single device. We discovered that binding of ATF1, but not of AP-1, to the CRE half-site is highly affected by its genomic context. This effect was highly correlated with ATF1 ChIP-seq and PBM experiments. Next, we characterized the affinities of ATF1 and ATF3 to 128 genomic CRE and CRE half-site sequences. Our affinity measurements explained that in vivo binding differences between ATF1 and ATF3 to CRE and CRE half-sites are partially mediated by differences in the minor groove width. We believe that QPID would become a central tool for quantitative characterization of biophysical aspects affecting protein-DNA binding.

Prophage recombinases-mediated genome engineering in Lactobacillus plantarum

BACKGROUND

Lactobacillus plantarum is a food-grade microorganism with industrial and medical relevance belonging to the group of lactic acid bacteria (LAB). Traditional strategies for obtaining gene deletion variants in this organism are mainly vector-based double-crossover methods, which are inefficient and laborious. A feasible possibility to solve this problem is the recombineering, which greatly expands the possibilities for engineering DNA molecules in vivo in various organisms.

RESULTS

In this work, a double-stranded DNA (dsDNA) recombineering system was established in L. plantarum. An exonuclease encoded by lp_0642 and a potential host-nuclease inhibitor encoded by lp_0640 involved in dsDNA recombination were identified from a prophage P1 locus in L. plantarum WCFS1. These two proteins, combined with the previously characterized single strand annealing protein encoded by lp_0641, can perform homologous recombination between a heterologous dsDNA substrate and host genomic DNA. Based on this, we developed a method for marker-free genetic manipulation of the chromosome in L. plantarum.

CONCLUSIONS

This Lp_0640-41-42-mediated recombination allowed easy screening of mutants and could serve as an alternative to other genetic manipulation methods. We expect that this method can help for understanding the probiotic functionality and physiology of LAB.

Hierarchical boosting: a machine-learning framework to detect and classify hard selective sweeps in human populations

MOTIVATION

Detecting positive selection in genomic regions is a recurrent topic in natural population genetic studies. However, there is little consistency among the regions detected in several genome-wide scans using different tests and/or populations. Furthermore, few methods address the challenge of classifying selective events according to specific features such as age, intensity or state (completeness).

RESULTS

We have developed a machine-learning classification framework that exploits the combined ability of some selection tests to uncover different polymorphism features expected under the hard sweep model, while controlling for population-specific demography. As a result, we achieve high sensitivity toward hard selective sweeps while adding insights about their completeness (whether a selected variant is fixed or not) and age of onset. Our method also determines the relevance of the individual methods implemented so far to detect positive selection under specific selective scenarios. We calibrated and applied the method to three reference human populations from The 1000 Genome Project to generate a genome-wide classification map of hard selective sweeps. This study improves detection of selective sweep by overcoming the classical selection versus no-selection classification strategy, and offers an explanation to the lack of consistency observed among selection tests when applied to real data. Very few signals were observed in the African population studied, while our method presents higher sensitivity in this population demography.

AVAILABILITY AND IMPLEMENTATION

The genome-wide results for three human populations from The 1000 Genomes Project and an R-package implementing the 'Hierarchical Boosting' framework are available at http://hsb.upf.edu/.

PatternQuery: web application for fast detection of biomacromolecular structural patterns in the entire Protein Data Bank

Well defined biomacromolecular patterns such as binding sites, catalytic sites, specific protein or nucleic acid sequences, etc. precisely modulate many important biological phenomena. We introduce PatternQuery, a web-based application designed for detection and fast extraction of such patterns. The application uses a unique query language with Python-like syntax to define the patterns that will be extracted from datasets provided by the user, or from the entire Protein Data Bank (PDB). Moreover, the database-wide search can be restricted using a variety of criteria, such as PDB ID, resolution, and organism of origin, to provide only relevant data. The extraction generally takes a few seconds for several hundreds of entries, up to approximately one hour for the whole PDB. The detected patterns are made available for download to enable further processing, as well as presented in a clear tabular and graphical form directly in the browser. The unique design of the language and the provided service could pave the way towards novel PDB-wide analyses, which were either difficult or unfeasible in the past. The application is available free of charge at http://ncbr.muni.cz/PatternQuery.

Establishing Chlamydomonas reinhardtii as an industrial biotechnology host

Microalgae constitute a diverse group of eukaryotic unicellular organisms that are of interest for pure and applied research. Owing to their natural synthesis of value-added natural products microalgae are emerging as a source of sustainable chemical compounds, proteins and metabolites, including but not limited to those that could replace compounds currently made from fossil fuels. For the model microalga, Chlamydomonas reinhardtii, this has prompted a period of rapid development so that this organism is poised for exploitation as an industrial biotechnology platform. The question now is how best to achieve this? Highly advanced industrial biotechnology systems using bacteria and yeasts were established in a classical metabolic engineering manner over several decades. However, the advent of advanced molecular tools and the rise of synthetic biology provide an opportunity to expedite the development of C. reinhardtii as an industrial biotechnology platform, avoiding the process of incremental improvement. In this review we describe the current status of genetic manipulation of C. reinhardtii for metabolic engineering. We then introduce several concepts that underpin synthetic biology, and show how generic parts are identified and used in a standard manner to achieve predictable outputs. Based on this we suggest that the development of C. reinhardtii as an industrial biotechnology platform can be achieved more efficiently through adoption of a synthetic biology approach.

Resilience of biochemical activity in protein domains in the face of structural divergence

Recent studies point to the prevalence of the evolutionary phenomenon of drastic structural transformation of protein domains while continuing to preserve their basic biochemical function. These transformations span a wide spectrum, including simple domains incorporated into larger structural scaffolds, changes in the structural core, major active site shifts, topological rewiring and extensive structural transmogrifications. Proteins from biological conflict systems, such as toxin-antitoxin, restriction-modification, CRISPR/Cas, polymorphic toxin and secondary metabolism systems commonly display such transformations. These include endoDNases, metal-independent RNases, deaminases, ADP ribosyltransferases, immunity proteins, kinases and E1-like enzymes. In eukaryotes such transformations are seen in domains involved in chromatin-related peptide recognition and protein/DNA-modification. Intense selective pressures from 'arms-race'-like situations in conflict and macromolecular modification systems could favor drastic structural divergence while preserving function.