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At least 469 records · Page 26

Strengths and Limitations of 16S rRNA Gene Amplicon Sequencing in Revealing Temporal Microbial Community Dynamics

This study explored the short-term planktonic microbial community structure and resilience in Lake Lanier (GA, USA) while simultaneously evaluating the technical aspects of identifying taxa via 16S rRNA gene amplicon and metagenomic sequence data. 16S rRNA gene amplicons generated from four temporally discrete samples were sequenced with 454 GSFLX-Ti yielding ~40,000 rRNA gene sequences from each sample and representing ~300 observed OTUs. Replicates obtained from the same biological sample clustered together but several biases were observed, linked to either the PCR or sequencing-preparation steps. In comparisons with companion whole-community shotgun metagenome datasets, the estimated number of OTUs at each timepoint was concordant, but 1.5 times and ~10 times as many phyla and genera, respectively, were identified in the metagenomes. Our analyses showed that the 16S rRNA gene captures broad shifts in community diversity over time, but with limited resolution and lower sensitivity compared to metagenomic data. We also identified OTUs that showed marked shifts in abundance over four close timepoints separated by perturbations and tracked these taxa in the metagenome vs. 16S rRNA amplicon data. A strong summer storm had less of an effect on community composition than did seasonal mixing, which revealed a distinct succession of organisms. This study provides insights into freshwater microbial communities and advances the approaches for assessing community diversity and dynamics in situ.

59 BASIC BIOLOGICAL SCIENCES↗

Molecular characterization of sulfate-reducing bacteria in the Guaymas Basin

The Guaymas Basin (Gulf of California) is a hydrothermal vent site where thermal alteration of deposited planktonic and terrestrial organic matter forms petroliferous material which supports diverse sulfate-reducing bacteria. We explored the phylogenetic and functional diversity of the sulfate-reducing bacteria by characterizing PCR-amplified dissimilatory sulfite reductase (dsrAB) and 16S rRNA genes from the upper 4 cm of the Guaymas sediment. The dsrAB sequences revealed that there was a major clade closely related to the acetate-oxidizing delta-proteobacterial genus Desulfobacter and a clade of novel, deeply branching dsr sequences related to environmental dsr sequences from marine sediments in Aarhus Bay and Kysing Fjord (Denmark). Other dsr clones were affiliated with gram-positive thermophilic sulfate reducers (genus Desulfotomaculum) and the delta-proteobacterial species Desulforhabdus amnigena and Thermodesulforhabdus norvegica. Phylogenetic analysis of 16S rRNAs from the same environmental samples resulted in identification of four clones affiliated with Desulfobacterium niacini, a member of the acetate-oxidizing, nutritionally versatile genus Desulfobacterium, and one clone related to Desulfobacula toluolica and Desulfotignum balticum. Other bacterial 16S rRNA bacterial phylotypes were represented by non-sulfate reducers and uncultured lineages with unknown physiology, like OP9, OP8, as well as a group with no clear affiliation. In summary, analyses of both 16S rRNA and dsrAB clone libraries resulted in identification of members of the Desulfobacteriales in the Guaymas sediments. In addition, the dsrAB sequencing approach revealed a novel group of sulfate-reducing prokaryotes that could not be identified by 16S rRNA sequencing.

Non-programmatic↗

Pseudouridinylation of mRNA coding sequences alters translation

Chemical modifications of RNAs have long been established as key modulators of nonprotein-coding RNA structure and function in cells. There is a growing appreciation that messenger RNA (mRNA) sequences responsible for directing protein synthesis can also be posttranscriptionally modified. The enzymatic incorporation of mRNA modifications has many potential outcomes, including changing mRNA stability, protein recruitment, and translation. In this work, we tested how one of the most common modifications present in mRNA coding regions, pseudouridine (Ψ), impacts protein synthesis using a fully reconstituted bacterial translation system and human cells. Our work reveals that replacing a single uridine nucleotide with Ψ in an mRNA codon impedes amino acid addition and EF-Tu GTPase activation. A crystal structure of the Thermus thermophilus 70S ribosome with a tRNA Phe bound to a ΨUU codon in the A site supports these findings. We also find that the presence of Ψ can promote the low-level synthesis of multiple peptide products from a single mRNA sequence in the reconstituted translation system as well as human cells, and increases the rate of near-cognate Val-tRNA Val reacting on a ΨUU codon. The vast majority of Ψ moieties in mRNAs are found in coding regions, and our study suggests that one consequence of the ribosome encountering Ψ can be to modestly alter both translation speed and mRNA decoding.

59 BASIC BIOLOGICAL SCIENCES↗

Drosophila Nanos acts as a molecular clamp that modulates the RNA-binding and repression activities of Pumilio

Collaboration among the multitude of RNA-binding proteins (RBPs) is ubiquitous, yet our understanding of these key regulatory complexes has been limited to single RBPs. We investigated combinatorial translational regulation by Drosophila Pumilio (Pum) and Nanos (Nos), which control development, fertility, and neuronal functions. Our results show how the specificity of one RBP (Pum) is modulated by cooperative RNA recognition with a second RBP (Nos) to synergistically repress mRNAs. Crystal structures of Nos-Pum-RNA complexes reveal that Nos embraces Pum and RNA, contributes sequence-specific contacts, and increases Pum RNA-binding affinity. Nos shifts the recognition sequence and promotes repression complex formation on mRNAs that are not stably bound by Pum alone, explaining the preponderance of sub-optimal Pum sites regulated in vivo . Our results illuminate the molecular mechanism of a regulatory switch controlling crucial gene expression programs, and provide a framework for understanding how the partnering of RBPs evokes changes in binding specificity that underlie regulatory network dynamics.

Weidmann, Chase A.↗

Proteogenomic characterization of difficult-to-treat breast cancer with tumor cells enriched through laser microdissection

Abstract Background Breast cancer (BC) is the most commonly diagnosed cancer and the leading cause of cancer death among women globally. Despite advances, there is considerable variation in clinical outcomes for patients with non-luminal A tumors, classified as difficult-to-treat breast cancers (DTBC). This study aims to delineate the proteogenomic landscape of DTBC tumors compared to luminal A (LumA) tumors. Methods We retrospectively collected a total of 117 untreated primary breast tumor specimens, focusing on DTBC subtypes. Breast tumors were processed by laser microdissection (LMD) to enrich tumor cells. DNA, RNA, and protein were simultaneously extracted from each tumor preparation, followed by whole genome sequencing, paired-end RNA sequencing, global proteomics and phosphoproteomics. Differential feature analysis, pathway analysis and survival analysis were performed to better understand DTBC and investigate biomarkers. Results We observed distinct variations in gene mutations, structural variations, and chromosomal alterations between DTBC and LumA breast tumors. DTBC tumors predominantly had more mutations inTP53,PLXNB3, Zinc finger genes, and fewer mutations inSDC2,CDH1,PIK3CA,SVIL, andPTEN. Notably, Cytoband 1q21, which contains numerous cell proliferation-related genes, was significantly amplified in the DTBC tumors. LMD successfully minimized stromal components and increased RNA–protein concordance, as evidenced by stromal score comparisons and proteomic analysis. Distinct DTBC and LumA-enriched clusters were observed by proteomic and phosphoproteomic clustering analysis, some with survival differences. Phosphoproteomics identified two distinct phosphoproteomic profiles for high relapse-risk and low relapse-risk basal-like tumors, involving several genes known to be associated with breast cancer oncogenesis and progression, includingKIAA1522,DCK,FOXO3,MYO9B,ARID1A,EPRS,ZC3HAV1, andRBM14. Lastly, an integrated pathway analysis of multi-omics data highlighted a robust enrichment of proliferation pathways in DTBC tumors. Conclusions This study provides an integrated proteogenomic characterization of DTBC vs LumA with tumor cells enriched through laser microdissection. We identified many common features of DTBC tumors and the phosphopeptides that could serve as potential biomarkers for high/low relapse-risk basal-like BC and possibly guide treatment selections.

Oncology↗

Comprehensive Assessments of RNA-seq by the SEQC Consortium: FDA-Led Efforts Advance Precision Medicine

Studies on gene expression in response to therapy have led to the discovery of pharmacogenomics biomarkers and advances in precision medicine. Whole transcriptome sequencing (RNA-seq) is an emerging tool for profiling gene expression and has received wide adoption in the biomedical research community. However, its value in regulatory decision making requires rigorous assessment and consensus between various stakeholders, including the research community, regulatory agencies, and industry. The FDA-led SEquencing Quality Control (SEQC) consortium has made considerable progress in this direction, and is the subject of this review. Specifically, three RNA-seq platforms (Illumina HiSeq, Life Technologies SOLiD, and Roche 454) were extensively evaluated at multiple sites to assess cross-site and cross-platform reproducibility. The results demonstrated that relative gene expression measurements were consistently comparable across labs and platforms, but not so for the measurement of absolute expression levels. As part of the quality evaluation several studies were included to evaluate the utility of RNA-seq in clinical settings and safety assessment. The neuroblastoma study profiled tumor samples from 498 pediatric neuroblastoma patients by both microarray and RNA-seq. RNA-seq offers more utilities than microarray in determining the transcriptomic characteristics of cancer. However, RNA-seq and microarray-based models were comparable in clinical endpoint prediction, even when including additional features unique to RNA-seq beyond gene expression. The toxicogenomics study compared microarray and RNA-seq profiles of the liver samples from rats exposed to 27 different chemicals representing multiple toxicity modes of action. Cross-platform concordance was dependent on chemical treatment and transcript abundance. Though both RNA-seq and microarray are suitable for developing gene expression based predictive models with comparable prediction performance, RNA-seq offers advantages over microarray in profiling genes with low expression. The rat BodyMap study provided a comprehensive rat transcriptomic body map by performing RNA-Seq on 320 samples from 11 organs in either sex of juvenile, adolescent, adult and aged Fischer 344 rats. Lastly, the transferability study demonstrated that signature genes of predictive models are reciprocally transferable between microarray and RNA-seq data for model development using a comprehensive approach with two large clinical data sets. This result suggests continued usefulness of legacy microarray data in the coming RNA-seq era. In conclusion, the SEQC project enhances our understanding of RNA-seq and provides valuable guidelines for RNA-seq based clinical application and safety evaluation to advance precision medicine.

59 BASIC BIOLOGICAL SCIENCES↗

Transcriptomic Data Sets for Zymomonas mobilis 2032 during Fermentation of Ammonia Fiber Expansion (AFEX)-Pretreated Corn Stover and Switchgrass Hydrolysates

The transcriptomes of Zymomonas mobilis 2032 were captured during the fermentation of ammonia fiber expansion (AFEX)-pretreated corn stover and switchgrass hydrolysates containing different concentrations of glucose and xylose. RNA samples were collected when Z. mobilis was fermenting glucose or xylose. Here, we present transcriptome sequencing (RNA-Seq) data obtained during separate phases of glucose or xylose consumption.

59 BASIC BIOLOGICAL SCIENCES↗

The “Most Wanted” Taxa from the Human Microbiome for Whole Genome Sequencing

The goal of the Human Microbiome Project (HMP) is to generate a comprehensive catalog of human-associated microorganisms including reference genomes representing the most common species. Toward this goal, the HMP has characterized the microbial communities at 18 body habitats in a cohort of over 200 healthy volunteers using 16S rRNA gene (16S) sequencing and has generated nearly 1,000 reference genomes from human-associated microorganisms. To determine how well current reference genome collections capture the diversity observed among the healthy microbiome and to guide isolation and future sequencing of microbiome members, we compared the HMP’s 16S data sets to several reference 16S collections to create a ‘most wanted’ list of taxa for sequencing. Our analysis revealed that the diversity of commonly occurring taxa within the HMP cohort microbiome is relatively modest, few novel taxa are represented by these OTUs and many common taxa among HMP volunteers recur across different populations of healthy humans. Taken together, these results suggest that it should be possible to perform whole-genome sequencing on a large fraction of the human microbiome, including the ‘most wanted’, and that these sequences should serve to support microbiome studies across multiple cohorts. Also, in stark contrast to other taxa, the ‘most wanted’ organisms are poorly represented among culture collections suggesting that novel culture- and single-cell-based methods will be required to isolate these organisms for sequencing.

59 BASIC BIOLOGICAL SCIENCES↗

The Epsomitic Phototrophic Microbial Mat of Hot Lake, Washington. Community Structural Responses to Seasonal Cycling

Phototrophic microbial mats are compact ecosystems composed of highly interactive organisms in which energy and element cycling take place over millimeter-to-centimeter-scale distances. Although microbial mats are common in hypersaline environments, they have not been extensively characterized in systems dominated by divalent ions. Hot Lake is a meromictic, epsomitic lake that occupies a small, endorheic basin in north-central Washington. The lake harbors a benthic, phototrophic mat that assembles each spring, disassembles each fall, and is subject to greater than tenfold variation in salinity (primarily Mg 2+ and SO 2 -4 ) and irradiation over the annual cycle. We examined spatiotemporal variation in the mat community at five time points throughout the annual cycle with respect to prevailing physicochemical parameters by amplicon sequencing of the V4 region of the 16S rRNA gene coupled to near-full-length 16S RNA clone sequences. The composition of these microbial communities was relatively stable over the seasonal cycle and included dominant populations of Cyanobacteria, primarily a group IV cyanobacterium (Leptolyngbya), and Alphaproteobacteria (specifically, members of Rhodobacteraceae and Geminicoccus). Members of Gammaproteobacteria (e.g., Thioalkalivibrio and Halochromatium) and Deltaproteobacteria (e.g., Desulfofustis) that are likely to be involved in sulfur cycling peaked in summer and declined significantly by mid-fall, mirroring larger trends in mat community richness and evenness. Phylogenetic turnover analysis of abundant phylotypes employing environmental metadata suggests that seasonal shifts in light variability exert a dominant influence on the composition of Hot Lake microbial mat communities. The seasonal development and organization of these structured microbial mats provide opportunities for analysis of the temporal and physical dynamics that feed back to community function.

16S tag sequencing↗

Radiation Stability Evaluation of Protein-Based Nanopores for Mars and Europa Missions

Exploration of our Solar System has revealed a number of locations that are now habitable or could have supported life in the past. One approach to finding life involves detection of informational polymers like deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) that are definitive biosignatures for life as we know it. Alternatively, structural variants of DNA and RNA, collectively termed xenonucleic acids (XNAs) have been shown in the laboratory to behave similarly. Nanopore-based sequencers differ from traditional sequencing technologies in that they do not explicitly require synthesis of DNA before or during analysis. Because of this, nanopore sequencers have been used for the direct sequencing of RNA, and could be used for the detection and analysis of other charged polymers. Here we describe results of exposing the MinION hardware, flow cells, and key reagents to ionizing radiation at doses relevant to Mars and Europa missions (10 to 3000 silicon-equivalent gray).

Burton, Aaron S.↗

Co-conservation of rRNA tetraloop sequences and helix length suggests involvement of the tetraloops in higher-order interactions

Terminal loops containing four nucleotides (tetraloops) are common in structural RNAs, and they frequently conform to one of three sequence motifs, GNRA, UNCG, or CUUG. Here we compare available sequences and secondary structures for rRNAs from bacteria, and we show that helices capped by phylogenetically conserved GNRA loops display a strong tendency to be of conserved length. The simplest interpretation of this correlation is that the conserved GNRA loops are involved in higher-order interactions, intramolecular or intermolecular, resulting in a selective pressure for maintaining the lengths of these helices. A small number of conserved UNCG loops were also found to be associated with conserved length helices, consistent with the possibility that this type of tetraloop also takes part in higher-order interactions.

Non-NASA Center↗

A chromosome-level genome assembly of the Chinese cork oak (Quercus variabilis)

Quercus variabilis (Fagaceae) is an ecologically and economically important deciduous broadleaved tree species native to and widespread in East Asia. It is a valuable woody species and an indicator of local forest health, and occupies a dominant position in forest ecosystems in East Asia. However, genomic resources from Q. variabilis are still lacking. Here, we present a high-quality Q. variabilis genome generated by PacBio HiFi and Hi-C sequencing. The assembled genome size is 787 Mb, with a contig N50 of 26.04 Mb and scaffold N50 of 64.86 Mb, comprising 12 pseudo-chromosomes. The repetitive sequences constitute 67.6% of the genome, of which the majority are long terminal repeats, accounting for 46.62% of the genome. We used ab initio , RNA sequence-based and homology-based predictions to identify protein-coding genes. A total of 32,466 protein-coding genes were identified, of which 95.11% could be functionally annotated. Evolutionary analysis showed that Q. variabilis was more closely related to Q. suber than to Q. lobata or Q. robur. We found no evidence for species-specific whole genome duplications in Quercus after the species had diverged. This study provides the first genome assembly and the first gene annotation data for Q. variabilis. These resources will inform the design of further breeding strategies, and will be valuable in the study of genome editing and comparative genomics in oak species.

Han, Biao↗

Methods and compositions for controlling gene expression by RNA processing

The present disclosure provides nucleic acids encoding an RNA recognition sequence positioned proximal to an insertion site for the insertion of a sequence of interest; and host cells genetically modified with the nucleic acids. The present disclosure also provides methods of modifying the activity of a target RNA, and kits and compositions for carrying out the methods.

59 BASIC BIOLOGICAL SCIENCES↗

Comparing variability in diagnosis of upper respiratory tract infections in patients using syndromic, next generation sequencing, and PCR-based methods

Early and accurate diagnosis of respiratory pathogens and associated outbreaks can allow for the control of spread, epidemiological modeling, targeted treatment, and decision making–as is evident with the current COVID-19 pandemic. Many respiratory infections share common symptoms, making them difficult to diagnose using only syndromic presentation. Yet, with delays in getting reference laboratory tests and limited availability and poor sensitivity of point-of-care tests, syndromic diagnosis is the most-relied upon method in clinical practice today. Here, we examine the variability in diagnostic identification of respiratory infections during the annual infection cycle in northern New Mexico, by comparing syndromic diagnostics with polymerase chain reaction (PCR) and sequencing-based methods, with the goal of assessing gaps in our current ability to identify respiratory pathogens. Of 97 individuals that presented with symptoms of respiratory infection, only 23 were positive for at least one RNA virus, as confirmed by sequencing. Whereas influenza virus (n = 7) was expected during this infection cycle, we also observed coronavirus (n = 7), respiratory syncytial virus (n = 8), parainfluenza virus (n = 4), and human metapneumovirus (n = 1) in individuals with respiratory infection symptoms. Four patients were coinfected with two viruses. In 21 individuals that tested positive using PCR, RNA sequencing completely matched in only 12 (57%) of these individuals. Few individuals (37.1%) were diagnosed to have an upper respiratory tract infection or viral syndrome by syndromic diagnostics, and the type of virus could only be distinguished in one patient. Thus, current syndromic diagnostic approaches fail to accurately identify respiratory pathogens associated with infection and are not suited to capture emerging threats in an accurate fashion. We conclude there is a critical and urgent need for layered agnostic diagnostics to track known and unknown pathogens at the point of care to control future outbreaks.

60 APPLIED LIFE SCIENCES↗

In search of autophagy biomarkers in breast cancer: Receptor status and drug agnostic transcriptional changes during autophagy flux in cell lines

Autophagy drives drug resistance and drug-induced cancer cell cytotoxicity. Targeting the autophagy process could greatly improve chemotherapy outcomes. The discovery of specific inhibitors or activators has been hindered by challenges with reliably measuring autophagy levels in a clinical setting. We investigated drug-induced autophagy in breast cancer cell lines with differing ER/PR/Her2 receptor status by exposing them to known but divergent autophagy inducers each with a unique molecular target, tamoxifen, trastuzumab, bortezomib or rapamycin. Differential gene expression analysis from total RNA extracted during the earliest sign of autophagy flux showed both cell- and drug-specific changes. We analyzed the list of differentially expressed genes to find a common, cell- and drug-agnostic autophagy signature. Twelve mRNAs were significantly modulated by all the drugs and 11 were orthogonally verified with Q-RT-PCR (Klhl24, Hbp1, Crebrf, Ypel2, Fbxo32, Gdf15, Cdc25a, Ddit4, Psat1, Cd22, Ypel3). The drug agnostic mRNA signature was similarly induced by a mitochondrially targeted agent, MitoQ. In-silico analysis on the KM-plotter cancer database showed that the levels of these mRNAs are detectable in human samples and associated with breast cancer prognosis outcomes of Relapse-Free Survival in all patients (RSF), Overall Survival in all patients (OS), and Relapse-Free Survival in ER + Patients (RSF ER + ). High levels of Klhl24, Hbp1, Crebrf, Ypel2, CD22 and Ypel3 were correlated with better outcomes, whereas lower levels of Gdf15, Cdc25a, Ddit4 and Psat1 were associated with better prognosis in breast cancer patients. This gene signature uncovers candidate autophagy biomarkers that could be tested during preclinical and clinical studies to monitor the autophagy process.

60 APPLIED LIFE SCIENCES↗

RolyPoly (rp) v0.1.0

The Rolypoly pipeline is designed to process raw RNA-seq data and identify potential RNA viral sequences. It is split into several self contained steps: 1. input data filtering and QC, 2. Genome assembly and refinement, 3. Assembly filtering, 4. Mapping to known RNA viral genomes, 5. Searching for RNA viral marker genes. 6. Genome functional and structural annotation. 6. Report preparation and potential downstream analysis The last module, may include taxonomic assignment, host range estimation, and phenotypic prediction. There are many similar software, but they focus on human related viruses, and lack the downstream applications or differ in their sensitivity. The initial user base are non-computational microbial ecologists who wish to better understand the potential RNA viruses in their own generated samples.

Neri, Uri↗

RNA Crystallization

RNA molecules may be crystallized using variations of the methods developed for protein crystallography. As the technology has become available to syntheisize and purify RNA molecules in the quantities and with the quality that is required for crystallography, the field of RNA structure has exploded. The first consideration when crystallizing an RNA is the sequence, which may be varied in a rational way to enhance crystallizability or prevent formation of alternate structures. Once a sequence has been designed, the RNA may be synthesized chemically by solid-state synthesis, or it may be produced enzymatically using RNA polymerase and an appropriate DNA template. Purification of milligram quantities of RNA can be accomplished by HPLC or gel electrophoresis. As with proteins, crystallization of RNA is usually accomplished by vapor diffusion techniques. There are several considerations that are either unique to RNA crystallization or more important for RNA crystallization. Techniques for design, synthesis, purification, and crystallization of RNAs will be reviewed here.

Golden, Barbara L.↗

Identifying RNA contacts from SHAPE-MaP by partial correlation analysis

In a recent paper Siegfried et al. published a new sequence-based structural RNA assay that utilizes mutational profiling to detect base pairing (MaP). Output from MaP provides information about both pairing (via reactivities) and contact (via correlations). Reactivities can be coupled to partition function folding models for structural inference, while correlations can reveal pairs of sites that may be in structural proximity. The possibility for inference of 3D contacts via MaP suggests a novel approach to structural prediction for RNA analogous to covariance structural prediction for proteins. We explore this approach and show that partial correlation analysis outperforms na\"ive correlation analysis. Our results should be applicable to a wide range of high-throughput sequencing based RNA structural assays that are under development.

Tambe, Akshay↗