Biophysical analysis of Pseudomonas-phage PaP3 small terminase suggests a mechanism for sequence-spe
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Niazi, Marzia↗
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Results for “sequence analysis”
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FUN-PROSE: A deep learning approach to predict condition-specific gene expression in fungi
mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important to metabolically engineer these organisms to produce desired chemicals in industrially scalable conditions. Most previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE—a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on three fungal species and get the correlation between predicted and observed condition-specific gene expression as high as 0.85. We then interpret our model to extract promoter sequence motifs responsible for variable expression of individual genes. We also carried out input feature importance analysis to connect individual transcription factors to their gene targets. A sizeable fraction of both sequence motifs and TF-gene interactions learned by our model agree with previously known biological information, while the rest corresponds to either novel biological facts or indirect correlations.
59 BASIC BIOLOGICAL SCIENCES↗
Genome Sequencing of Cladobotryum protrusum Provides Insights into the Evolution and Pathogenic Mechanisms of the Cobweb Disease Pathogen on Cultivated Mushroom
Cladobotryum protrusum is one of the mycoparasites that cause cobweb disease on cultivated edible mushrooms. However, the molecular mechanisms of evolution and pathogenesis of C. protrusum on mushrooms are largely unknown. Here, we report a high-quality genome sequence of C. protrusum using the single-molecule, real-time sequencing platform of PacBio and perform a comparative analysis with closely related fungi in the family Hypocreaceae. The C. protrusum genome, the first complete genome to be sequenced in the genus Cladobotryum, is 39.09 Mb long, with an N50 of 4.97 Mb, encoding 11,003 proteins. The phylogenomic analysis confirmed its inclusion in Hypocreaceae, with its evolutionary divergence time estimated to be ~170.1 million years ago. The genome encodes a large and diverse set of genes involved in secreted peptidases, carbohydrate-active enzymes, cytochrome P450 enzymes, pathogen–host interactions, mycotoxins, and pigments. Moreover, C. protrusum harbors arrays of genes with the potential to produce bioactive secondary metabolites and stress response-related proteins that are significant for adaptation to hostile environments. Knowledge of the genome will foster a better understanding of the biology of C. protrusum and mycoparasitism in general, as well as help with the development of effective disease control strategies to minimize economic losses from cobweb disease in cultivated edible mushrooms.
60 APPLIED LIFE SCIENCES↗
Exploration of Noncoding Sequences in Metagenomes
Environment-dependent genomic features have been defined for different metagenomes, whose genes and their associated processes are related to specific environments. Identification of ORFs and their functional categories are the most common methods for association between functional and environmental features. However, this analysis based on finding ORFs misses noncoding sequences and, therefore, some metagenome regulatory or structural information could be discarded. In this work we analyzed 23 whole metagenomes, including coding and noncoding sequences using the following sequence patterns: (G+C) content, Codon Usage (Cd), Trinucleotide Usage (Tn), and functional assignments for ORF prediction. Herein, we present evidence of a high proportion of noncoding sequences discarded in common similarity based methods in metagenomics, and the kind of relevant information present in those. We found a high density of trinucleotide repeat sequences (TRS) in noncoding sequences, with a regulatory and adaptive function for metagenome communities. We present associations between trinucleotide values and gene function, where metagenome clustering correlate with microorganism adaptations and kinds of metagenomes. We propose here that noncoding sequences have relevant information to describe metagenomes that could be considered in a whole metagenome analysis in order to improve their organization, classification protocols, and their relation with the environment.
59 BASIC BIOLOGICAL SCIENCES↗
Applications and challenges of forensic proteomics
Mass spectrometry-based proteomics has been a useful tool for addressing numerous questions in basic biology research for many years. This success, combined with the maturity of mass spectrometric instrumentation, the ever-increasing availability of protein sequence databases derived from genome sequencing, and the growing sophistication of data analysis methods, places proteomics in a position to have an important role in biological forensics. Because proteins contain information about genotype (sequence) and phenotype (expression levels), proteomics methods can both identify biological samples and characterize the conditions that produced them. In addition to serving as a valuable orthogonal method to genomic analyses, proteomics can be used in cases where nucleic acids are absent, degraded, or uninformative. Mass spectrometry provides both broad applicability and exquisite specificity, often without customized detection reagents like primers or antibodies. This review briefly introduces proteomics methods, and surveys a variety of forensic applications (including criminal justice, historical, archaeological, and national security areas). Finally, challenges and crucial areas for further research are addressed.
forensics, proteomics, mass spectrometry, protein,↗
The MAVRIC-Shift Sequence in SCALE for Radiation Transport and Shielding Calculations with Automated Variance Reduction and Parallel Computing
A new MAVRIC-Shift sequence has been implemented and tested within the SCALE Code System to provide parallel computing capabilities for radiation transport and shielding analysis with automated variance reduction. This new sequence provides the most widely used capabilities of the MAVRIC sequence and also features the highly scalable Shift Monte Carlo solver, thus enabling faster time-to-solution when run on multiple cores. This report provides a summary of the theory of variance reduction approaches in MAVRIC and the integration of Shift into the MAVRIC sequence of SCALE. Similarities and differences in methodologies between the traditional MAVRIC sequence and the new MAVRIC-Shift sequence are discussed. Validation cases are presented with models of radiation shielding experiments and verification is provided with a series of practical application cases of interest to the US Nuclear Regulatory Commission, the sponsors of this work, including spent nuclear fuel transportation and storage systems.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Five key aspects of metaproteomics as a tool to understand functional interactions in host-associated microbiomes
Host-associated microbial communities (microbiomes) play critical roles in human, animal, and plant health and development. However, interactions between the host, members of the microbiome, and invading pathogens are in most cases still poorly understood. Such interactions are multidimensional and can alter the taxonomic composition and/or the functional metabolic activities of the microbiome in response to disease or treatment conditions. For example, after 2 days of antibiotic treatment, the mouse gut microbiome is altered and more susceptible to invasion by the pathogen Clostridioides difficile. Studies of these multidimensional interactions have been fueled by the ability to use high-throughput sequencing of phylogenetic marker genes to profile microbial community composition and shotgun metagenomics to profile functional potential. However, many protein-coding genes predicted from metagenomes are not necessarily expressed under a given condition, and thus, it is difficult to assess the activities and functional interactions in microbial communities based on DNA sequencing data alone. The physiological and pathological processes expressed in these communities under specific conditions are better reflected by the abundances of transcripts or proteins. In this Pearl, we provide a brief introduction to metaproteomics, which is a tool for the large-scale analysis of proteins in microbiomes that allows researchers to address a diversity of questions related to functions and interactions in microbiomes. The term “metaproteomics” was first used in 2004 for “the large-scale characterization of the entire protein complement of environmental microbiota at a given point in time”, and since then, a large array of metaproteomics approaches have been developed. Our objective in this Pearl is to highlight what we feel are 5 essential elements to be considered for a metaproteomics research campaign and to introduce nonexpert readers to the topic without going into too much technical detail.
59 BASIC BIOLOGICAL SCIENCES↗
Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network
Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism.
59 BASIC BIOLOGICAL SCIENCES↗
The parallelism motifs of genomic data analysis
Genomic datasets are growing dramatically as the cost of sequencing continues to decline and small sequencing devices become available. Enormous community databases store and share these data with the research community, but some of these genomic data analysis problems require large-scale computational platforms to meet both the memory and computational requirements. These applications differ from scientific simulations that dominate the workload on high-end parallel systems today and place different requirements on programming support, software libraries and parallel architectural design. For example, they involve irregular communication patterns such as asynchronous updates to shared data structures. We consider several problems in high-performance genomics analysis, including alignment, profiling, clustering and assembly for both single genomes and metagenomes. We identify some of the common computational patterns or ‘motifs’ that help inform parallelization strategies and compare our motifs to some of the established lists, arguing that at least two key patterns, sorting and hashing, are missing. This article is part of a discussion meeting issue ‘Numerical algorithms for high-performance computational science’.
59 BASIC BIOLOGICAL SCIENCES↗
Revealing the transcriptomic complexity of switchgrass by PacBio long-read sequencing
Switchgrass ( Panicum virgatum L.) is an important bioenergy crop widely used for lignocellulosic research. While extensive transcriptomic analyses have been conducted on this species using short read-based sequencing techniques, very little has been reliably derived regarding alternatively spliced (AS) transcripts. Here, we present an analysis of transcriptomes of six switchgrass tissue types pooled together, sequenced using Pacific Biosciences (PacBio) single-molecular long-read technology. Our analysis identified 105,419 unique transcripts covering 43,570 known genes and 8795 previously unknown genes. 45,168 are novel transcripts of known genes. A total of 60,096 AS transcripts are identified, 45,628 being novel. We have also predicted 1549 transcripts of genes involved in cell wall construction and remodeling, 639 being novel transcripts of known cell wall genes. Most of the predicted transcripts are validated against Illumina-based short reads. Specifically, 96% of the splice junction sites in all the unique transcripts are validated by at least five Illumina reads. Comparisons between genes derived from our identified transcripts and the current genome annotation revealed that among the gene set predicted by both analyses, 16,640 have different exon-intron structures. Overall, substantial amount of new information is derived from the PacBio RNA data regarding both the transcriptome and the genome of switchgrass.
09 BIOMASS FUELS↗
Limited genetic diversity across pathogen populations responsible for the global emergence of boxwood blight identified using SSR s
Boxwood blight is an emerging disease of ornamental as well as native boxwood. The disease became widely established in Europe at the beginning of the 21st century, prior to its more recent discovery in North America and Asia. Two sister‐species of fungi cause the disease, Calonectria pseudonaviculata (Cps) and C. henricotiae (Che). Prior efforts to quantify intraspecific genetic polymorphisms of Cps and Che have yielded little information, limiting the ability to understand the evolution and migration of these pathogens. This study describes the development and implementation of simple sequence repeat ( SSR ) markers to analyse genetic diversity from a global collection of Cps and Che isolates, representing major blight outbreaks since the disease was first identified in the UK in the late 1990s. Analysis of the Cps CB 002 genome sequence identified 180 single copy SSR loci using stringent search criteria, 11 of which were polymorphic and used to screen a global sample of 306 isolates. Fourteen multilocus genotypes of Cps and two multilocus genotypes of Che were identified. Twelve of the 14 Cps genotypes differed from each other by a single allele. The most common Cps genotype was found on all continents where boxwood blight is confirmed. Based on measurement of linkage disequilibrium, Cps showed no evidence of sexual recombination. Further in silico analysis identified 1594 SSR s using relaxed SSR definition criteria. Comparison of these SSR ‐containing loci with Cps and Che genome sequences representing three different genotypes demonstrated that single nucleotide polymorphisms might serve as informative genetic markers for future studies.
LeBlanc, N.↗
Predicting the chemical space of fungal polyketides by phylogeny-based bioinformatics analysis of polyketide synthase-nonribosomal peptide synthetase and its modification enzymes
Fungal polyketide synthase (PKS)–nonribosomal peptide synthetase (NRPS) hybrids are key enzymes for synthesizing structurally diverse hybrid natural products (NPs) with characteristic biological activities. Predicting their chemical space is of particular importance in the field of natural product chemistry. However, the unexplored programming rule of the PKS module has prevented prediction of its chemical structure based on amino acid sequences. Here, we conducted a phylogenetic analysis of 884 PKS–NRPS hybrids and a modification enzyme analysis of the corresponding biosynthetic gene cluster, revealing a hidden relationship between its genealogy and core structures. This unexpected result allowed us to predict 18 biosynthetic gene cluster (BGC) groups producing known carbon skeletons (number of BGCs; 489) and 11 uncharacterized BGC groups (171). The limited number of carbon skeletons suggests that fungi tend to select PK skeletons for survival during their evolution. The possible involvement of a horizontal gene transfer event leading to the diverse distribution of PKS–NRPS genes among fungal species is also proposed. This study provides insight into the chemical space of fungal PKs and the distribution of their biosynthetic gene clusters.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
VRC34-Antibody Lineage Development Reveals How a Required Rare Mutation Shapes the Maturation of a Broad HIV-Neutralizing Lineage
Rare mutations have been proposed to restrict the development of broadly neutralizing antibodies against HIV-1, but this has not been explicitly demonstrated. We hypothesized that such rare mutations might be identified by comparing broadly neutralizing and non-broadly neutralizing branches of an antibody-developmental tree. Because sequences of antibodies isolated from the fusion peptide (FP)-targeting VRC34-antibody lineage suggested it might be suitable for such rare mutation analysis, we carried out next-generation sequencing (NGS) on B cell transcripts from donor N123, the source of the VRC34 lineage, and functionally and structurally characterized inferred intermediates along broadly neutralizing and poorly neutralizing developmental branches. The broadly neutralizing VRC34.01 branch required the rare heavy-chain mutation Y33P to bind FP, whereas the early bifurcated VRC34.05 branch did not require this rare mutation and evolved less breadth. Our results demonstrate how a required rare mutation can restrict development and shape the maturation of a broad HIV-1-neutralizing antibody lineage.
59 BASIC BIOLOGICAL SCIENCES↗
Transcriptome sequencing of three Pseudo-nitzschia species reveals comparable gene sets and the presence of Nitric Oxide Synthase genes in diatoms
Diatoms are among the most diverse eukaryotic microorganisms on Earth, they are responsible for a large fraction of primary production in the oceans and can be found in different habitats. Pseudo-nitzschia are marine planktonic diatoms responsible for blooms in coastal and oceanic waters. We analyzed the transcriptome of three species, Pseudo-nitzschia arenysensis, Pseudo-nitzschia delicatissima and Pseudo-nitzschia multistriata, with different levels of genetic relatedness. These species have a worldwide distribution and the last one produces the neurotoxin domoic acid. We were able to annotate about 80% of the sequences in each transcriptome and the analysis of the relative functional annotations allowed comparison of the main metabolic pathways, pathways involved in the biosynthesis of isoprenoids (MAV and MEP pathways) and pathways putatively involved in domoic acid synthesis. The search for homologous transcripts among the target species and other congeneric species resulted in the discovery of a sequence annotated as Nitric Oxide Synthase (NOS), found uniquely in Pseudo-nitzschia multistriata. The predicted protein product contained all the domains of the canonical metazoan sequence. Putative NOS sequences were found in other available diatom datasets, supporting a role for nitric oxide as signaling molecule in this group of microalgae.
59 BASIC BIOLOGICAL SCIENCES↗
Genomic analysis of six new Geobacillus strains reveals highly conserved carbohydrate degradation architectures and strategies
In this work we report the whole genome sequences of six new Geobacillus xylanolytic strains along with the genomic analysis of their capability to degrade carbohydrates. The six sequenced Geobacillus strains described here have a range of GC contents from 43.9% to 52.5% and clade with named Geobacillus species throughout the entire genus. We have identified a ~200 kb unique super-cluster in all six strains, containing five to eight distinct carbohydrate degradation clusters in a single genomic region, a feature not seen in other genera. The Geobacillus strains rely on a small number of secreted enzymes located within distinct clusters for carbohydrate utilization, in contrast to most biomass-degrading organisms which contain numerous secreted enzymes located randomly throughout the genomes. All six strains are able to utilize fructose, arabinose, xylose, mannitol, gluconate, xylan, and α-1,6-glucosides. The gene clusters for utilization of these seven substrates have identical organization and the individual proteins have a high percent identity to their homologs. The strains show significant differences in their ability to utilize inositol, sucrose, lactose, α-mannosides, α-1,4-glucosides and arabinan.
59 BASIC BIOLOGICAL SCIENCES↗
Development of peptoid-based ligands for the removal of cadmium from biological media
Cadmium poisoning poses a serious health concern due to cadmium's increasing industrial use, yet there is currently no recommended treatment. The selective coordination of cadmium in a biological environment—i.e. in the presence of serum ions, small molecules, and proteins—is a difficult task. To address this challenge, a combinatorial library of peptoid-based ligands has been evaluated to identify structures that selectively bind to cadmium in human serum with minimal chelation of essential metal ions. Eighteen unique ligands were identified in this screening procedure, and the binding affinity of each was measured using metal titrations monitored by UV-vis spectroscopy. To evaluate the significance of each chelating moiety, sequence rearrangements and substitutions were examined. Analysis of a metal–ligand complex by NMR spectroscopy highlighted the importance of particular residues. Depletion experiments were performed in serum mimetics and human serum with exogenously added cadmium. These depletion experiments were used to compare and demonstrate the ability of these peptoids to remove cadmium from blood-like mixtures. In one of these depletion experiments, the peptoid sequence was able to deplete the cadmium to a level comparable to the reported acute toxicity limit. Evaluation of the metal selectivity in buffered solution and in human serum was performed to verify minimal off-target binding. These studies highlight a screening platform for the identification of metal–ligands that are capable of binding in a complex environment. They additionally demonstrate the potential utility of biologically-compatible ligands for the treatment of heavy metal poisoning.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Cacao pod transcriptome profiling of seven genotypes identifies features associated with post-penetration resistance to Phytophthora palmivora
Abstract The oomycete Phytophthora palmivora infects the fruit of cacao trees ( Theobroma cacao ) causing black pod rot and reducing yields. Cacao genotypes vary in their resistance levels to P. palmivora , yet our understanding of how cacao fruit respond to the pathogen at the molecular level during disease establishment is limited. To address this issue, disease development and RNA-Seq studies were conducted on pods of seven cacao genotypes (ICS1, WFT, Gu133, Spa9, CCN51, Sca6 and Pound7) to better understand their reactions to the post-penetration stage of P. palmivora infection. The pod tissue- P. palmivora pathogen assay resulted in the genotypes being classified as susceptible (ICS1, WFT, Gu133 and Spa9) or resistant (CCN51, Sca6 and Pound7). The number of differentially expressed genes (DEGs) ranged from 1625 to 6957 depending on genotype. A custom gene correlation approach identified 34 correlation groups. De novo motif analysis was conducted on upstream promoter sequences of differentially expressed genes, identifying 76 novel motifs, 31 of which were over-represented in the upstream sequences of correlation groups and associated with gene ontology terms related to oxidative stress response, defense against fungal pathogens, general metabolism and cell function. Genes in one correlation group (Group 6) were strongly induced in all genotypes and enriched in genes annotated with defense-responsive terms. Expression pattern profiling revealed that genes in Group 6 were induced to higher levels in the resistant genotypes. An additional analysis allowed the identification of 17 candidate cis -regulatory modules likely to be involved in cacao defense against P. palmivora . This study is a comprehensive exploration of the cacao pod transcriptional response to P. palmivora spread after infection. We identified cacao genes, promoter motifs, and promoter motif combinations associated with post-penetration resistance to P. palmivora in cacao pods and provide this information as a resource to support future and ongoing efforts to breed P. palmivora -resistant cacao.
60 APPLIED LIFE SCIENCES↗
Establishing Data Analysis Pipeline for Bulk ATAC-Seq Datasets
We developed an analysis pipeline for transposase-accessible chromatin sequencing (ATAC-Seq) data derived from bulk samples, which brings together publicly available R packages in addition to command-line tools designed for analysis of bulk ATAC-Seq data and can be run on any computer running a Linux-like operating system such as Ubuntu or Apple OSX.
97 MATHEMATICS AND COMPUTING↗