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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

SARS-CoV-2 wastewater variant surveillance: pandemic response leveraging FDA’s GenomeTrakr network

ABSTRACT Wastewater surveillance has emerged as a crucial public health tool for population-level pathogen surveillance. Supported by funding from the American Rescue Plan Act of 2021, the FDA‘s genomic epidemiology program, GenomeTrakr, was leveraged to sequence SARS-CoV-2 from wastewater sites across the United States. This initiative required the evaluation, optimization, development, and publication of new methods and analytical tools spanning sample collection through variant analyses. Version-controlled protocols for each step of the process were developed and published on protocols.io. A custom data analysis tool and a publicly accessible dashboard were built to facilitate real-time visualization of the collected data, focusing on the relative abundance of SARS-CoV-2 variants and sub-lineages across different samples and sites throughout the project. From September 2021 through June 2023, a total of 3,389 wastewater samples were collected, with 2,517 undergoing sequencing and submission to NCBI under the umbrella BioProject,PRJNA757291. Sequence data were released with explicit quality control (QC) tags on all sequence records, communicating our confidence in the quality of data. Variant analysis revealed wide circulation of Delta in the fall of 2021 and captured the sweep of Omicron and subsequent diversification of this lineage through the end of the sampling period. This project successfully achieved two important goals for the FDA’s GenomeTrakr program: first, contributing timely genomic data for the SARS-CoV-2 pandemic response, and second, establishing both capacity and best practices for culture-independent, population-level environmental surveillance for other pathogens of interest to the FDA. IMPORTANCE This paper serves two primary objectives. First, it summarizes the genomic and contextual data collected during a Covid-19 pandemic response project, which utilized the FDA’s laboratory network, traditionally employed for sequencing foodborne pathogens, for sequencing SARS-CoV-2 from wastewater samples. Second, it outlines best practices for gathering and organizing population-level next generation sequencing (NGS) data collected for culture-free, surveillance of pathogens sourced from environmental samples.

Microbiology↗
DOE OSTI2021

The Effects of Herbarium Specimen Characteristics on Short-Read NGS Sequencing Success in Nearly 8000 Specimens: Old, Degraded Samples Have Lower DNA Yields but Consistent Sequencing Success

Phylogenetic datasets are now commonly generated using short-read sequencing technologies unhampered by degraded DNA, such as that often extracted from herbarium specimens. The compatibility of these methods with herbarium specimens has precipitated an increase in broad sampling of herbarium specimens for inclusion in phylogenetic studies. Understanding which sample characteristics are predictive of sequencing success can guide researchers in the selection of tissues and specimens most likely to yield good results. Multiple recent studies have considered the relationship between sample characteristics and DNA yield and sequence capture success. Here we report an analysis of the relationship between sample characteristics and sequencing success for nearly 8,000 herbarium specimens. This study, the largest of its kind, is also the first to include a measure of specimen quality (“greenness”) as a predictor of DNA sequencing success. We found that taxonomic group and source herbarium are strong predictors of both DNA yield and sequencing success and that the most important specimen characteristics for predicting success differ for DNA yield and sequencing: greenness was the strongest predictor of DNA yield, and age was the strongest predictor of proportion-on-target reads recovered. Surprisingly, the relationship between age and proportion-on-target reads is the inverse of expectations; older specimens performed slightly better in our capture-based protocols. We also found that DNA yield itself is not a strong predictor of sequencing success. Most literature on DNA sequencing from herbarium specimens considers specimen selection for optimal DNA extraction success, which we find to be an inappropriate metric for predicting success using next-generation sequencing technologies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

DIVA/DeviceEditor v6.1.2

DIVA is an end-to-end DNA design and construction management platform that streamlines how researchers design, build, and receive sequence-verified DNA constructs. Through a web-based BioCAD interface (DeviceEditor), researchers independently design DNA constructs and submit them to a centralized queue with a single action. Designs progress transparently through standardized states which allow researchers to track status and access finished constructs via a central DNA repository. Submitted designs are reviewed by dedicated staff for feasibility and optimization, reducing costly failures and improving downstream execution. Automated DNA assembly software optimizes construction strategies by reusing existing parts where possible and sourcing synthetic DNA only when needed. Standardized, sequence-agnostic assembly methods enable many independent constructs to be built in parallel using lab automation, dramatically increasing throughput. High-throughput next-generation sequencing is used to verify construct accuracy, with flexible platforms selected based on task requirements. Throughout the process, detailed success and failure data are captured and analyzed, enabling continuous improvement of assembly protocols. Compared to traditional, manual DNA construction workflows, DIVA offers higher scalability, transparency, reproducibility, and data-driven optimization.

Plahar, Hector [Lawrence Berkeley National Laborat↗
DOE OSTI2019

AI Meets Exascale Computing: Advancing Cancer Research With Large-Scale High Performance Computing

The application of data science in cancer research has been boosted by major advances in three primary areas: (1) Data: diversity, amount, and availability of biomedical data; (2) Advances in Artificial Intelligence (AI) and Machine Learning (ML) algorithms that enable learning from complex, large-scale data; and (3) Advances in computer architectures allowing unprecedented acceleration of simulation and machine learning algorithms. These advances help build in silico ML models that can provide transformative insights from data including: molecular dynamics simulations, next-generation sequencing, omics, imaging, and unstructured clinical text documents. Unique challenges persist, however, in building ML models related to cancer, including: (1) access, sharing, labeling, and integration of multimodal and multi-institutional data across different cancer types; (2) developing AI models for cancer research capable of scaling on next generation high performance computers; and (3) assessing robustness and reliability in the AI models. In this paper, we review the National Cancer Institute (NCI) -Department of Energy (DOE) collaboration, Joint Design of Advanced Computing Solutions for Cancer (JDACS4C), a multi-institution collaborative effort focused on advancing computing and data technologies to accelerate cancer research on three levels: molecular, cellular, and population. This collaboration integrates various types of generated data, pre-exascale compute resources, and advances in ML models to increase understanding of basic cancer biology, identify promising new treatment options, predict outcomes, and eventually prescribe specialized treatments for patients with cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

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↗
DOE OSTI2017

Metagenomic 16S rRNA Sequencing Analysis of Pacific Oyster (Crassostrea gigas) Microbiota from the Puget Sound Region in the United States

This is the first study analyzing Pacific oyster microbiota in the Puget Sound estuarine system using a next-generation sequencing method. Taxonomic analysis indicated that Tenericutes, Chlamydiae , Proteobacteria , and Firmicutes were the most abundant phyla. Small numbers of operational taxonomic units (OTUs) belonging to the Vibrio genus were detected in all the oyster microbiome samples.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Multiplex detection and identification of viral, bacterial, and protozoan pathogens in human blood and plasma using an expanded high-density resequencing microarray platform

Introduction: Nucleic acid tests for blood donor screening have improved the safety of the blood supply; however, increasing numbers of emerging pathogen tests are burdensome. Multiplex testing platforms are a potential solution. Methods: The Blood Borne Pathogen Resequencing Microarray Expanded (BBP-RMAv.2) can perform multiplex detection and identification of 80 viruses, bacteria and parasites. This study evaluated pathogen detection in human blood or plasma. Samples spiked with selected pathogens, each with one of 6 viruses, 2 bacteria and 5 protozoans were tested on this platform. The nucleic acids were extracted, amplified using multiplexed sets of primers, and hybridized to a microarray. The reported sequences were aligned to a database to identify the pathogen. To directly compare the microarray to an emerging molecular approach, the amplified nucleic acids were also submitted to nanopore next generation sequencing (NGS). Results: The BBP-RMAv.2 detected viral pathogens at a concentration as low as 100 copies/ml and a range of concentrations from 1,000 to 100,000 copies/ml for all the spiked pathogens. Coded specimens were identified correctly demonstrating the effectiveness of the platform. The nanopore sequencing correctly identified most samples and the results of the two platforms were compared. Discussion: These results indicated that the BBP-RMAv.2 could be employed for multiplex detection with potential for use in blood safety or disease diagnosis. The NGS was nearly as effective at identifying pathogens in blood and performed better than BBP-RMAv.2 at identifying pathogen-negative samples.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

High-throughput single-cell transcriptomics of bacteria using combinatorial barcoding

Microbial split-pool ligation transcriptomics (microSPLiT) is a high-throughput single-cell RNA sequencing method for bacteria. With four combinatorial barcoding rounds, microSPLiT can profile transcriptional states in hundreds of thousands of Gram-negative and Gram-positive bacteria in a single experiment without specialized equipment. As bacterial samples are fixed and permeabilized before barcoding, they can be collected and stored ahead of time. During the first barcoding round, the fixed and permeabilized bacteria are distributed into a 96-well plate, where their transcripts are reverse transcribed into cDNA and labeled with the first well-specific barcode inside the cells. The cells are mixed and redistributed two more times into new 96-well plates, where the second and third barcodes are appended to the cDNA via in-cell ligation reactions. Finally, the cells are mixed and divided into aliquot sub-libraries, which can be stored until future use or prepared for sequencing with the addition of a fourth barcode. It takes 4 days to generate sequencing-ready libraries, including 1 day for collection and overnight fixation of samples. Here, the standard plate setup enables single-cell transcriptional profiling of up to 1 million bacterial cells and up to 96 samples in a single barcoding experiment, with the possibility of expansion by adding barcoding rounds. The protocol requires experience in basic molecular biology techniques, handling of bacterial samples and preparation of DNA libraries for next-generation sequencing. It can be performed by experienced undergraduate or graduate students. Data analysis requires access to computing resources, familiarity with Unix command line and basic experience with Python or R.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A multiplexed bacterial two-hybrid for rapid characterization of protein–protein interactions and iterative protein design

Protein-protein interactions (PPIs) are crucial for biological functions and have applications ranging from drug design to synthetic cell circuits. Coiled-coils have been used as a model to study the sequence determinants of specificity. However, building well-behaved sets of orthogonal pairs of coiled-coils remains challenging due to inaccurate predictions of orthogonality and difficulties in testing at scale. To address this, we develop the next-generation bacterial two-hybrid (NGB2H) method, which allows for the rapid exploration of interactions of programmed protein libraries in a quantitative and scalable way using next-generation sequencing readout. We design, build, and test large sets of orthogonal synthetic coiled-coils, assayed over 8,000 PPIs, and used the dataset to train a more accurate coiled-coil scoring algorithm (iCipa). After characterizing nearly 18,000 new PPIs, we identify to the best of our knowledge the largest set of orthogonal coiled-coils to date, with fifteen on-target interactions. Our approach provides a powerful tool for the design of orthogonal PPIs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Single-molecule Real-time (SMRT) Isoform Sequencing (Iso-Seq) in Plants: The Status of the Bioinformatics Tools to Unravel the Transcriptome Complexity

Background: The advent of the Single-Molecule Real-time (SMRT) Isoform Sequencing(Iso-Seq) has paved the way to obtain longer full-length transcripts. This method was found tobe much superior in identifying full-length splice variants and other post-transcriptional events ascompared to the Next Generation Sequencing (NGS)-based short read sequencing (RNA-Seq).Several different bioinformatics tools to analyze the Iso-Seq data have been developed and someof them are still being refined to address different aspects of transcriptome complexity. However, acomprehensive summary of the available tools and their utility is still lacking. Objective: Here, we summarized the existing Iso-Seq analysis tools and presented an integratedbioinformatics pipeline for Iso-Seq analysis, which overcomes the limitations of NGS and generateslong contiguous Full-Length Non-Chimeric (FLNC) reads for the analysis of posttranscriptionalevents. Results: In this review, we summarized recent applications of Iso-Seq in plants, which include improvedgenome annotations, identification of novel genes and lncRNAs, identification of fulllengthsplice isoforms, detection of novel Alternative Splicing (AS) and Alternative Polyadenylation(APA) events. In addition, we also discussed the bioinformatics pipeline for comprehensiveIso-Seq data analysis, including how to reduce the error rate in the reads and how to identify andquantify post-transcriptional events. Furthermore, the visualization approach of Iso-Seq was discussedas well. Finally, we discussed methods to combine Iso-Seq data with RNA-Seq for transcriptomequantification. Conclusion: Overall, this review demonstrates that the Iso-Seq is pivotal for analyzing transcriptomecomplexity and this new method offers unprecedented opportunities to comprehensively understandtranscripts diversity.

Biochemistry & Molecular Biology↗
DOE OSTI2018

Alignment-free genome comparison enables accurate geographic sourcing of white oak DNA

Background: The application of genomic data and bioinformatics for the identification of restricted or illegally-sourced natural products is urgently needed. The taxonomic identity and geographic provenance of raw and processed materials have implications in sustainable-use commercial practices, and relevance to the enforcement of laws that regulate or restrict illegally harvested materials, such as timber. Improvements in genomics make it possible to capture and sequence partial-to-complete genomes from challenging tissues, such as wood and wood products. Results: In this paper, we report the success of an alignment-free genome comparison method, d 2; that differentiates different geographic sources of white oak (Quercus) species with a high level of accuracy with very small amount of genomic data. The method is robust to sequencing errors, different sequencing laboratories and sequencing platforms. Conclusions: This method offers an approach based on genome-scale data, rather than panels of pre-selected markers for specific taxa. The method provides a generalizable platform for the identification and sourcing of materials using a unified next generation sequencing and analysis framework.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Reinspection of a Clinical Proteomics Tumor Analysis Consortium (CPTAC) Dataset with Cloud Computing Reveals Abundant Post-Translational Modifications and Protein Sequence Variants

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) has provided some of the most in-depth analyses of the phenotypes of human tumors ever constructed. Today, the majority of proteomic data analysis is still performed using software housed on desktop computers which limits the number of sequence variants and post-translational modifications that can be considered. The original CPTAC studies limited the search for PTMs to only samples that were chemically enriched for those modified peptides. Similarly, the only sequence variants considered were those with strong evidence at the exon or transcript level. In this multi-institutional collaborative reanalysis, we utilized unbiased protein databases containing millions of human sequence variants in conjunction with hundreds of common post-translational modifications. Using these tools, we identified tens of thousands of high-confidence PTMs and sequence variants. We identified 4132 phosphorylated peptides in nonenriched samples, 93% of which were confirmed in the samples which were chemically enriched for phosphopeptides. In addition, our results also cover 90% of the high-confidence variants reported by the original proteogenomics study, without the need for sample specific next-generation sequencing. Finally, we report fivefold more somatic and germline variants that have an independent evidence at the peptide level, including mutations in ERRB2 and BCAS1. In this reanalysis of CPTAC proteomic data with cloud computing, we present an openly available and searchable web resource of the highest-coverage proteomic profiling of human tumors described to date.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

A compendium of multi-omic sequence information from the Saanich Inlet water column

Marine oxygen minimum zones (OMZs) are widespread regions of the ocean that are currently expanding due to global warming. While inhospitable to most metazoans, OMZs are hotspots for microbial mediated biogeochemical cycling of carbon, nitrogen and sulphur, contributing disproportionately to marine nitrogen loss and climate active trace gas production. Our current understanding of microbial community responses to OMZ expansion is limited by a lack of time-resolved data sets linking multi-omic sequence information (DNA, RNA, protein) to geochemical parameters and process rates. Here, we present six years of time-resolved multi-omic observations in Saanich Inlet, a seasonally anoxic fjord on the coast of Vancouver Island, British Columbia, Canada that undergoes recurring changes in water column oxygenation status. This compendium provides a unique multi-omic framework for studying microbial community responses to ocean deoxygenation along defined geochemical gradients in OMZ waters.

Hawley, Alyse K. (ORCID:0000000235164043)↗
DOE OSTI2017

New technologies accelerate the exploration of non-coding RNAs in horticultural plants

Non-coding RNAs (ncRNAs), that is, RNAs not translated into proteins, are crucial regulators of a variety of biological processes in plants. While protein-encoding genes have been relatively well-annotated in sequenced genomes, accounting for a small portion of the genome space in plants, the universe of plant ncRNAs is rapidly expanding. Recent advances in experimental and computational technologies have generated a great momentum for discovery and functional characterization of ncRNAs. Here we summarize the classification and known biological functions of plant ncRNAs, review the application of next-generation sequencing (NGS) technology and ribosome profiling technology to ncRNA discovery in horticultural plants and discuss the application of new technologies, especially the new genome-editing tool clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9) systems, to functional characterization of plant ncRNAs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

CasCollect: targeted assembly of CRISPR-associated operons from high-throughput sequencing data

Abstract CRISPR arrays and CRISPR-associated (Cas) proteins comprise a widespread adaptive immune system in bacteria and archaea. These systems function as a defense against exogenous parasitic mobile genetic elements that include bacteriophages, plasmids and foreign nucleic acids. With the continuous spread of antibiotic resistance, knowledge of pathogen susceptibility to bacteriophage therapy is becoming more critical. Additionally, gene-editing applications would benefit from the discovery of new cas genes with favorable properties. While next-generation sequencing has produced staggering quantities of data, transitioning from raw sequencing reads to the identification of CRISPR/Cas systems has remained challenging. This is especially true for metagenomic data, which has the highest potential for identifying novel cas genes. We report a comprehensive computational pipeline, CasCollect, for the targeted assembly and annotation of cas genes and CRISPR arrays—even isolated arrays—from raw sequencing reads. Benchmarking our targeted assembly pipeline demonstrates significantly improved timing by almost two orders of magnitude compared with conventional assembly and annotation, while retaining the ability to detect CRISPR arrays and cas genes. CasCollect is a highly versatile pipeline and can be used for targeted assembly of any specialty gene set, reconfigurable for user provided Hidden Markov Models and/or reference nucleotide sequences.

Podlevsky, Joshua D.↗
DOE OSTI2018

Phylogenetic patterns recover known HIV epidemiological relationships and reveal common transmission of multiple variants

The growth of human immunodeficiency virus (HIV) sequence databases resulting from drug resistance testing has motivated efforts using phylogenetic methods to assess how HIV spreads. Such inference is potentially both powerful and useful for tracking the epidemiology of HIV and the allocation of resources to prevention campaigns. We recently used simulation and a small number of illustrative cases to show that certain phylogenetic patterns are associated with different types of epidemiological linkage. Our original approach was later generalized for large next-generation sequencing datasets and implemented as a free computational pipeline. Previous work has claimed that direction and directness of transmission could not be established from phylogeny because one could not be sure that there were no intervening or missing links involved. We address this issue by investigating phylogenetic patterns from 272 previously identified HIV transmission chains with 955 transmission pairs representing diverse geography, risk groups, subtypes, and genomic regions. These HIV transmissions had known linkage based on epidemiological information such as partner studies, mother-to-child transmission, pairs identified by contact tracing, and criminal cases. Here, we show that the resulting phylogeny inferred from real HIV genetic sequences indeed reveals distinct patterns associated with direct transmission contra transmissions from a common source. Thus, our results establish how to interpret phylogenetic trees based on HIV sequences when tracking who-infected-whom, when and how genetic information can be used for improved tracking of HIV spread. We also investigate limitations that stem from limited sampling and genetic time-trends in the donor and recipient HIV populations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Network of epistatic interactions in an enzyme active site revealed by large-scale deep mutational scanning

Cooperative interactions between amino acids are critical for protein function. A genetic reflection of cooperativity is epistasis, which is when a change in the amino acid at one position changes the sequence requirements at another position. To assess epistasis within an enzyme active site, we utilized CTX-M β-lactamase as a model system. CTX-M hydrolyzes β-lactam antibiotics to provide antibiotic resistance, allowing a simple functional selection for rapid sorting of modified enzymes. We created all pairwise mutations across 17 active site positions in the β-lactamase enzyme and quantitated the function of variants against two β-lactam antibiotics using next-generation sequencing. Context-dependent sequence requirements were determined by comparing the antibiotic resistance function of double mutations across the CTX-M active site to their predicted function based on the constituent single mutations, revealing both positive epistasis (synergistic interactions) and negative epistasis (antagonistic interactions) between amino acid substitutions. The resulting trends demonstrate that positive epistasis is present throughout the active site, that epistasis between residues is mediated through substrate interactions, and that residues more tolerant to substitutions serve as generic compensators which are responsible for many cases of positive epistasis. Additionally, we show that a key catalytic residue (Glu166) is amenable to compensatory mutations, and we characterize one such double mutant (E166Y/N170G) that acts by an altered catalytic mechanism. These findings shed light on the unique biochemical factors that drive epistasis within an enzyme active site and will inform enzyme engineering efforts by bridging the gap between amino acid sequence and catalytic function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Circular RNA expression profiles in placental villi from women with gestational diabetes mellitus

Highlights: • More than 40,000 circRNAs are sequenced in the placental villi. • The expression profile of circRNAs in GDM is different from that in controls. • The potential effects of many differential circRNAs are involve in the development of GDM. • Some differential circRNAs have binding sites of GDM-related miRNAs. Circular RNAs (circRNAs) have recently been shown to exert their effects on multiple pathological processes by acting as microRNA (miRNA) sponges. However, the roles of circRNAs in gestational diabetes mellitus (GDM) are largely unknown. This study aimed to identify the circRNAs involved in GDM and predict their potential biological functions. We first performed next-generation sequencing (NGS) to generate unbiased placental villi circRNA expression profiles of GDM and normal controls. In total, 48,270 circRNAs from the placental villi of the two groups were sequenced. Of these, 227 circRNAs were significantly up-regulated and 255 circRNAs were significantly down-regulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathway analyses demonstrated that glycometabolism and lipometabolism processes, which are important in GDM development, were significantly enriched. Further analysis showed that most of the circRNAs harbored miRNA binding sites, and some were associated with GDM. These results showed that circRNAs are aberrantly expressed in the placental villi of GDM patients and play potential roles in the development of GDM.

60 APPLIED LIFE SCIENCES↗