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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Application of Whole Genome Sequencing and MALDI-TOF to the Identifcation of Bacillus Species Isolated from Cleanrooms at NASA Johnson Space Center

Astromaterial cleanrooms at NASA Johnson Space Center are built environments that hold samples, such as lunar rocks, from different space exploration missions. Bacillus sp. are frequently detected in routine microbial monitoring of these facilities. Since this, and related genera, can form endospores that can withstand harsh conditions, they could contaminate astromaterials. This could confound searches for extraterrestrial life. Whole genome sequencing (WGS) is widely used for identifying bacterial strains and tracking their source; however, WGS is expensive and time consuming. Matrix-assisted laser desorption ionization– time of flight mass spectrometry (MALDI-TOF) shows promise as a low-cost, rapid method of identifying strains of bacteria, but few studies have compared this proteomics method to WGS. To evaluate a high throughput method of tracking the source of contamination of this built environment, WGS and MALDI-TOF was conducted on 18 bacterial strains isolated from surfaces in astromaterials cleanrooms. WGS identified 14 Bacillus, 2 Paenibacillus, 1 Solibacillus and 1 Alcaligenes strains. These isolates showed similarity to strains commonly observed in spacecraft assembly cleanrooms at other facilities. Cluster analysis of mass spectra generated by MALDI-TOF grouped strains together that were greater than 94% similar to each other in terms of amino acid sequences of single copy core genes, as assessed by WGS. This suggests that MALDI-TOF and WGS results are consistent with each other and MALDI-TOF can rapidly identify strains of Bacillus sp. isolated from cleanroom environments with a resolution comparable to WGS. Based on phylogenomic analysis, these results also suggest the presence of a cosmopolitan class of Bacillus sp. that are more likely to be found in cleanrooms and similar built environments than in natural systems.

Farnaz Mazhari↗
DOE OSTI2025

Enhancing lipid production in plant cells through automated high-throughput genome engineering and phenotyping

Plant bioengineering is a time-consuming and labor-intensive process with no guarantee of achieving desired traits. Here, we present a fast, automated, scalable, high-throughput pipeline for plant bioengineering (FAST-PB) in maize (Zea mays) and Nicotiana benthamiana. FAST-PB enables genome editing and product characterization by integrating automated biofoundry engineering of callus and protoplast cells with single-cell matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). We first demonstrated that FAST-PB could streamline Golden Gate cloning, with the capacity to construct 96 vectors in parallel. Using FAST-PB in protoplasts, we found that PEG2050 increased transfection efficiency by over 45%. For proof-of-concept, we established a reporter-gene-free method for CRISPR editing and phenotyping via mutation of high chlorophyll fluorescence 136. We show that diverse lipids were enhanced up to 6-fold using CRISPR activation of lipid controlling genes. In callus cells, an automated transformation platform was employed to regenerate plants with enhanced lipid traits through introducing multigene cassettes. Lastly, FAST-PB enabled high-throughput single-cell lipid profiling by integrating MALDI-MS with the biofoundry, protoplast, and callus cells, differentiating engineered and unengineered cells using single-cell lipidomics. Furthermore, these innovations massively increase the throughput of synthetic biology, genome editing, and metabolic engineering and change what is possible using single-cell metabolomics in plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Data for Comparison of Genotyping Assays for Detection of Targeted CRISPR/Cas Mutagenesis in Highly Polyploid Sugarcane

Sugarcane ( Saccharum spp.) is an important biofuel feedstock and a leading source of global table sugar. Saccharum hybrid cultivars are highly polyploid (2n = 100–130), containing large numbers of functionally redundant hom(e)ologs in their genomes. Genome editing with sequence-specific nucleases holds tremendous promise for sugarcane breeding. However, identification of plants with the desired level of co-editing within a pool of primary transformants can be difficult. While DNA sequencing provides direct evidence of targeted mutagenesis, it is cost-prohibitive as a primary screening method in sugarcane and most other methods of identifying mutant lines have not been optimized for use in highly polyploid species. In this study, non-sequencing methods of mutant screening, including capillary electrophoresis (CE), Cas9 RNP assay, and high-resolution melt analysis (HRMA), were compared to assess their potential for CRISPR/Cas9-mediated mutant screening in sugarcane. These assays were used to analyze sugarcane lines containing mutations at one or more of six sgRNA target sites. All three methods distinguished edited lines from wild type, with co-mutation frequencies ranging from 2% to 100%. Cas9 RNP assays were able to identify mutant sugarcane lines with as low as 3.2% co-mutation frequency, and samples could be scored based on undigested band intensity. CE was highlighted as the most comprehensive assay, delivering precise information on both mutagenesis frequency and indel size to a 1 bp resolution across all six targets. This represents an economical and comprehensive alternative to sequencing-based genotyping methods which could be applied in other polyploid species.

Genomics↗
DOE OSTI2025

MINE: maximally informative next experiment—toward a new GWAS experimental design and methodology

Abstract The computational methodology of Genome Wide Association Studies (GWAS) currently has several limitations: (i) the number of observations (rows) on a quantitative trait tends to be smaller than the number of single nucleotide polymorphisms (SNPs) (columns) in the design matrix; (ii) each SNP is usually modeled separately, failing to acknowledge interaction between each other (ie epistasis); (iii) there is implicit linkage disequilibrium (LD) between neighboring SNPs due to their linkage. To overcome these issues, we developed a tool that uses ensemble methods to fit mixed linear models to GWAS data, and these ensemble methods include the development of a new experimental design approach in GWAS, which uses the resultant models and data to select the next informative experiment over time. This new adaptive and staged approach for GWAS experimental design was developed and tested in a 3 yr adaptive model-guided discovery experiment against a fixed classical design. In Sorghum bicolor a total of 79, 86, and 78 accessions were tested in years 1, 2, and 3, respectively out of 343 accessions available in the Bioenergy Association Panel (BAP) each identified for 232,303 SNPs, 1 every 2–3 kb in the genomes. We demonstrated the feasibility of MINE enacted with 8 people in the field per year over 3 yr vs in 1 large classical design enacted with 20 people in 1 yr. The MINE results for chromosomal regions identified controlling dry weight were confirmed against results from previous sorghum GWAS experiments and 1 large classical design for the BAP panel.

Genetics & Heredity↗
NASA NTRS1994

Heavy ion induced DNA-DSB in yeast and mammalian cells

Molecular changes at the DNA are assumed to be the main cause for radiation effects in a number of organisms. During the course of the last decades techniques have been developed for measuring DNA double-strand breaks (dsb), generally assumed to be the most critical DNA lesions. The outcome of all those different approaches portrays a collection of data useful for a theoretical description of radiation action mechanisms. However, in the case of heavy ion induced DNA dsb the picture is not quite clear yet and further projects and strategies have to be developed. The biological systems studied in our group are yeast and mammalian cells. While in the case of yeast cells technical and methodical reasons highlight these organisms mammalian cells reach greater importance when dsb repair studies are performed. In both types of organisms the technique of pulsed-field gel electrophoresis (PFGE) is applied, although with different modifications and evaluation procedures mainly due to the different genome sizes.

Loebrich, M.↗
NASA NTRS2004

Complex Chromosomal Rearrangements Induced in Vivo by Heavy Ions

It has been suggested that the ratio complex/simple exchanges can be used as a biomarker of exposure to high-LET radiation. We tested this hypothesis in vivo, by considering data from several studies that measured complex exchanges in peripheral blood from humans exposed to mixed fields of low- and high-LET radiation. In particular, we studied data from astronauts involved in long-term missions in low-Earth-orbit, and uterus cancer patients treated with accelerated carbon ions. Data from two studies of chromosomal aberrations in astronauts used blood samples obtained before and after space flight, and a third study used blood samples from patients before and after radiotherapy course. Similar methods were used in each study, where lymphocytes were stimulated to grow in vitro, and collected after incubation in either colcemid or calyculin A. Slides were painted with whole-chromosome DNA fluorescent probes (FISH), and complex and simple chromosome exchanges in the painted genome were classified separately. Complex-type exchanges were observed at low frequencies in control subjects, and in our test subjects before the treatment. No statistically significant increase in the yield of complex-type exchanges was induced by the space flight. Radiation therapy induced a high fraction of complex exchanges, but no significant differences could be detected between patients treated with accelerated carbon ions or X-rays. Complex chromosomal rearrangements do not represent a practical biomarker of radiation quality in our test subjects. Copyright 2003 S. Karger AG, Basel.

Ions/adverse effects/therapeutic use↗
DOE OSTI2020

A genetic toolbox for metabolic engineering of Issatchenkia orientalis

The nonconventional yeast Issatchenkia orientalis can grow under highly acidic conditions and has been explored for production of various organic acids. Yet, its broader application is hampered by the lack of efficient genetic tools to enable sophisticated metabolic manipulations. We recently constructed an episomal plasmid based on the autonomously replicating sequence (ARS) from Saccharomyces cerevisiae (ScARS) in I. orientalis and developed a CRISPR/Cas9 system for multiplexed gene deletions. Here we report three additional genetic tools including: (1) identification of a 0.8 kb centromere-like (CEN-L) sequence from the I. orientalis genome by using bioinformatics and functional screening; (2) discovery and characterization of a set of constitutive promoters and terminators under different culture conditions by using RNA-Seq analysis and a fluorescent reporter; and (3) development of a rapid and efficient in vivo DNA assembly method in I. orientalis, which exhibited ~100% fidelity when assembling a 7 kb-plasmid from seven DNA fragments ranging from 0.7 kb to 1.7 kb. As evidence of concept, we used these genetic tools to rapidly construct a functional xylose utilization pathway in I. orientalis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program

The study aims to determine the shared genetic architecture between COVID-19 severity with existing medical conditions using electronic health record (EHR) data. We conducted a Phenome-Wide Association Study (PheWAS) of genetic variants associated with critical illness (n = 35) or hospitalization (n = 42) due to severe COVID-19 using genome-wide association summary data from the Host Genetics Initiative. PheWAS analysis was performed using genotype-phenotype data from the Veterans Affairs Million Veteran Program (MVP). Phenotypes were defined by International Classification of Diseases (ICD) codes mapped to clinically relevant groups using published PheWAS methods. Among 658,582 Veterans, variants associated with severe COVID-19 were tested for association across 1,559 phenotypes. Variants at the ABO locus (rs495828, rs505922) associated with the largest number of phenotypes (n rs495828 = 53 and n rs505922 = 59); strongest association with venous embolism, odds ratio (OR rs495828 1.33 (p = 1.32 x 10 –199 ), and thrombosis OR rs505922 1.33, p = 2.2 x10 -265 . Among 67 respiratory conditions tested, 11 had significant associations including MUC5B locus (rs35705950) with increased risk of idiopathic fibrosing alveolitis OR 2.83, p = 4.12 × 10 –191 ; CRHR1 (rs61667602) associated with reduced risk of pulmonary fibrosis, OR 0.84, p = 2.26× 10 –12 . The TYK2 locus (rs11085727) associated with reduced risk for autoimmune conditions, e.g., psoriasis OR 0.88, p = 6.48 x10 -23 , lupus OR 0.84, p = 3.97 x 10 –06 . PheWAS stratified by ancestry demonstrated differences in genotype-phenotype associations. LMNA (rs581342) associated with neutropenia OR 1.29 p = 4.1 x 10 –13 among Veterans of African and Hispanic ancestry but not European. Overall, we observed a shared genetic architecture between COVID-19 severity and conditions related to underlying risk factors for severe and poor COVID-19 outcomes. Differing associations between genotype-phenotype across ancestries may inform heterogenous outcomes observed with COVID-19. Divergent associations between risk for severe COVID-19 with autoimmune inflammatory conditions both respiratory and non-respiratory highlights the shared pathways and fine balance of immune host response and autoimmunity and caution required when considering treatment targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Coupling flux balance analysis with reactive transport modeling through machine learning for rapid and stable simulation of microbial metabolic switching

Integrating genome-scale metabolic networks with reactive transport models (RTMs) provides a detailed description of the dynamic changes in microbial growth and metabolism. Despite promising demonstrations in the past, computational inefficiency has been pointed out as a critical issue to overcome because it requires repeated application of linear programming (LP) to obtain flux balance analysis (FBA) solutions in every time step and spatial grid. To address this challenge, we propose a new simulation method where we train and validate artificial neural networks (ANNs) using randomly sampled FBA solutions and incorporate the resulting surrogate FBA model (represented as algebraic equations) into RTMs as source/sink terms. We demonstrate the efficiency of our method via a case study of Shewanella oneidensis MR-1. During aerobic growth on lactate, S. oneidensis produces metabolic byproducts (such as pyruvate and acetate), which are subsequently consumed as alternative carbon sources when the preferred nutrients are depleted. To effectively simulate these complex dynamics, we used a cybernetic approach that models metabolic switches as the outcome of dynamic competition among multiple growth options. In both zero-dimensional batch and one-dimensional column configurations, the ANN-based surrogate models achieved substantial reduction of computational time by several orders of magnitude compared to the original LP-based FBA models. Moreover, the ANN models produced robust solutions without any special measures to prevent numerical instability. These developments significantly promote our ability to utilize genome-scale networks in complex, multi-physics, and multi-dimensional ecosystem modeling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

An expanded registry of candidate cis -regulatory elements

Mammalian genomes contain millions of regulatory elements that control the complex patterns of gene expression. Previously, the ENCODE consortium mapped biochemical signals across hundreds of cell types and tissues and integrated these data to develop a registry containing 0.9 million human and 300,000 mouse candidate cis-regulatory elements (cCREs) annotated with potential functions. Here we have expanded the registry to include 2.37 million human and 967,000 mouse cCREs, leveraging new ENCODE datasets and enhanced computational methods. This expanded registry covers hundreds of unique cell and tissue types, providing a comprehensive understanding of gene regulation. Functional characterization data from assays such as STARR-seq, massively parallel reporter assay, CRISPR perturbation and transgenic mouse assays have profiled more than 90% of human cCREs, revealing complex regulatory functions. We identified thousands of novel silencer cCREs and demonstrated their dual enhancer and silencer roles in different cellular contexts. Integrating the registry with other ENCODE annotations facilitates genetic variation interpretation and trait-associated gene identification, exemplified by the identification of KLF1 as a novel causal gene for red blood cell traits. This expanded registry is a valuable resource for studying the regulatory genome and its impact on health and disease.

Moore, Jill E. [Univ. of Massachusetts, Worchester↗
DOE OSTI2021

2019 Computing Sciences Strategic Plan

Computing has transformed nearly every aspect of scientific inquiry — across disciplines and across scales — from the behavior of subatomic particles to the formation of structures in the early universe, from the assembly of the human genome to the evolution of earth systems. Over the past two decades, computing has become an integral part of how Berkeley Lab is “Bringing Science Solutions to the World.” Advances in computing and mathematics have been key, with new mathematical models of complex physical phenomena, new methods for analyzing complex data, new algorithms for accuracy and scaling and sophisticated software systems that encapsulate these techniques into open, reusable tools. The performance of NERSC computers and the ESnet network have grown by several orders of magnitude, along with our understanding of how to map scientific computations and workflows onto these systems. From research to facility operations, the passion, talent and dedication of the Computing Sciences Area staff has been the cornerstone of our success. The plan outlined in this document describes the next step in a journey to expand the influence and impact of our efforts, building an increasingly connected global enterprise for science that places more powerful instruments in the hands of scientists, along with more powerful methods and tools for modeling, analysis and prediction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Bacterial Bioleaching and Biorecovery for Biomining Unconventional Rare Earth Element Feedstocks

Bacterial metabolic interactions with rare earth elements (REEs) can be harnessed for biomining unconventional feedstocks like abandoned coal-mine drainage (AMD). Pennsylvania has ~500 AMD passive remediation systems that can precipitate REE rich solids. REEs include yttrium and the lanthanide series that are used in modern energy and technology. Bacteria that metabolically interact with REEs can be used for biomining in an affordable efficient process that does not require hazardous chemical additives. Currently, the microbial metal mechanisms that contribute to REE biorelease and biorecovery are poorly understood. Our work shows acidogenic bacterial isolates (Bacillus mycoides JR07 and Bacillus pseudomycoides KB7) successfully bioleach a mixed REE solution from AMD solids by their organic acid production and biofilm formation. Further, our work shows the potential for bacterial lanthanide-dependent enzymes to recover lanthanides from a mixed REE solution; here we have bacterial isolate Methylobacterium sp. B3 that can recover soluble lanthanum. Whole genome sequencing of Methylobacterium sp. B3 predict lanthanide-dependent methanol dehydrogenase XoxF. Understanding the microbial metabolism and genes involved in the REE release and recovery is crucial to optimize the biomining of AMD solids. Our work addresses the growing need to develop novel REE mining methods from unconventional feedstocks.

biogeochemistry↗
NASA NTRS2001

Better, Cheaper, Faster Molecular Dynamics

Recent, revolutionary progress in genomics and structural, molecular and cellular biology has created new opportunities for molecular-level computer simulations of biological systems by providing vast amounts of data that require interpretation. These opportunities are further enhanced by the increasing availability of massively parallel computers. For many problems, the method of choice is classical molecular dynamics (iterative solving of Newton's equations of motion). It focuses on two main objectives. One is to calculate the relative stability of different states of the system. A typical problem that has' such an objective is computer-aided drug design. Another common objective is to describe evolution of the system towards a low energy (possibly the global minimum energy), "native" state. Perhaps the best example of such a problem is protein folding. Both types of problems share the same difficulty. Often, different states of the system are separated by high energy barriers, which implies that transitions between these states are rare events. This, in turn, can greatly impede exploration of phase space. In some instances this can lead to "quasi non-ergodicity", whereby a part of phase space is inaccessible on time scales of the simulation. To overcome this difficulty and to extend molecular dynamics to "biological" time scales (millisecond or longer) new physical formulations and new algorithmic developments are required. To be efficient they should account for natural limitations of multi-processor computer architecture. I will present work along these lines done in my group. In particular, I will focus on a new approach to calculating the free energies (stability) of different states and to overcoming "the curse of rare events". I will also discuss algorithmic improvements to multiple time step methods and to the treatment of slowly decaying, log-ranged, electrostatic effects.

Pohorille, Andrew↗
NASA NTRS2004

A genomic timescale of prokaryote evolution: insights into the origin of methanogenesis, phototrophy, and the colonization of land

BACKGROUND: The timescale of prokaryote evolution has been difficult to reconstruct because of a limited fossil record and complexities associated with molecular clocks and deep divergences. However, the relatively large number of genome sequences currently available has provided a better opportunity to control for potential biases such as horizontal gene transfer and rate differences among lineages. We assembled a data set of sequences from 32 proteins (approximately 7600 amino acids) common to 72 species and estimated phylogenetic relationships and divergence times with a local clock method. RESULTS: Our phylogenetic results support most of the currently recognized higher-level groupings of prokaryotes. Of particular interest is a well-supported group of three major lineages of eubacteria (Actinobacteria, Deinococcus, and Cyanobacteria) that we call Terrabacteria and associate with an early colonization of land. Divergence time estimates for the major groups of eubacteria are between 2.5-3.2 billion years ago (Ga) while those for archaebacteria are mostly between 3.1-4.1 Ga. The time estimates suggest a Hadean origin of life (prior to 4.1 Ga), an early origin of methanogenesis (3.8-4.1 Ga), an origin of anaerobic methanotrophy after 3.1 Ga, an origin of phototrophy prior to 3.2 Ga, an early colonization of land 2.8-3.1 Ga, and an origin of aerobic methanotrophy 2.5-2.8 Ga. CONCLUSIONS: Our early time estimates for methanogenesis support the consideration of methane, in addition to carbon dioxide, as a greenhouse gas responsible for the early warming of the Earths' surface. Our divergence times for the origin of anaerobic methanotrophy are compatible with highly depleted carbon isotopic values found in rocks dated 2.8-2.6 Ga. An early origin of phototrophy is consistent with the earliest bacterial mats and structures identified as stromatolites, but a 2.6 Ga origin of cyanobacteria suggests that those Archean structures, if biologically produced, were made by anoxygenic photosynthesizers. The resistance to desiccation of Terrabacteria and their elaboration of photoprotective compounds suggests that the common ancestor of this group inhabited land. If true, then oxygenic photosynthesis may owe its origin to terrestrial adaptations.

Methane/metabolism↗
DOE OSTI2026

Empirical evaluation of all unique Cas9 protospacers in E. coli reveal widespread functionality and rules for gRNA design

The Cas9 nuclease has become central to modern methods and technologies in synthetic biology, largely due to the ease with which it can be targeted to specific DNA loci via guide RNAs (gRNAs). Reports vary widely on the actual specificity of this targeting, with some studies observing 60% of gRNAs possessing no activity against the genome, yet an assumption persists within the E. coli community that inactive gRNAs are rare. To resolve these contradictions, we evaluated the activity of 463 000 unique gRNAs in the E. coli K12 MG1655 genome. We show that the overwhelming majority (at least 93%) of unique gRNAs are functional while only 0.3% are nonfunctional. These nonfunctional gRNAs exhibit strong spacer self-interaction, which can either be excluded using a simple design rule or “repaired” during library design. Finally, this work provides the greater microbial synthetic biology community both a set of nearly half a million empirically evaluated E. coli gRNAs as well as a thoroughly evaluated experimental procedure, complete with appropriate controls for Cas9 activity, for conducting Cas9 assays in E. coli specifically and bacteria more generally. Lastly, we have produced a webapp to allow users to easily browse and extract gRNA sequences from the E. coli genome, which can be accessed at https://grna.ornl.gov.

Kammerdiener, Elise K. [Oak Ridge National Laborat↗
DOE OSTI2021

CRISPR-mediated multigene integration enables Shikimate pathway refactoring for enhanced 2-phenylethanol biosynthesis in Kluyveromyces marxianus

Background: 2-phenylethanol (2-PE) is a rose-scented flavor and fragrance compound that is used in food, beverages, and personal care products. Compatibility with gasoline also makes it a potential biofuel or fuel additive. A biochemical process converting glucose or other fermentable sugars to 2-PE can potentially provide a more sustainable and economical production route than current methods that use chemical synthesis and/or isolation from plant material. Results: We work toward this goal by engineering the Shikimate and Ehrlich pathways in the stress-tolerant yeast Kluyveromyces marxianus. First, we develop a multigene integration tool that uses CRISPR-Cas9 induced breaks on the genome as a selection for the one-step integration of an insert that encodes one, two, or three gene expression cassettes. Integration of a 5-kbp insert containing three overexpression cassettes successfully occurs with an efficiency of 51 ± 9% at the ABZ1 locus and was used to create a library of K. marxianus CBS 6556 strains with refactored Shikimate pathway genes. The 3 3 -factorial library includes all combinations of KmARO4, KmARO7, and KmPHA2, each driven by three different promoters that span a wide expression range. Analysis of the refactored pathway library reveals that high expression of the tyrosine-deregulated KmARO4 K221L and native KmPHA2, with the medium expression of feedback insensitive KmARO7 G141S , results in the highest increase in 2-PE biosynthesis, producing 684 ± 73 mg/L. Ehrlich pathway engineering by overexpression of KmARO10 and disruption of KmEAT1 further increases 2-PE production to 766 ± 6 mg/L. The best strain achieves 1943 ± 63 mg/L 2-PE after 120 h fed-batch operation in shake flask cultures. Conclusions: The CRISPR-mediated multigene integration system expands the genome-editing toolset for K. marxianus, a promising multi-stress tolerant host for the biosynthesis of 2-PE and other aromatic compounds derived from the Shikimate pathway.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Probing interspecies metabolic interactions within a synthetic binary microbiome using genome-scale modeling

Metabolic interactions within a microbial community play a key role in determining the structure, function, and composition of the community. However, due to the complexity and intractability of natural microbiomes, limited knowledge is available on interspecies interactions within a community. In this work, using a binary synthetic microbiome, a methanotroph-photoautotroph (M-P) coculture, as the model system, we examined different genome-scale metabolic modeling (GEM) approaches to gain a better understanding of the metabolic interactions within the coculture, how they contribute to the enhanced growth observed in the coculture, and how they evolve over time. Using batch growth data of the model M-P coculture, we compared three GEM approaches for microbial communities. Two of the methods are existing approaches: SteadyCom, a steady state GEM, and dynamic flux balance analysis (DFBA) Lab, a dynamic GEM. We also proposed an improved dynamic GEM approach, DynamiCom, for the M-P coculture. SteadyCom can predict the metabolic interactions within the coculture but not their dynamic evolutions; DFBA Lab can predict the dynamics of the coculture but cannot identify interspecies interactions. DynamiCom was able to identify the cross-fed metabolite within the coculture, as well as predict the evolution of the interspecies interactions over time. A new dynamic GEM approach, DynamiCom, was developed for a model M-P coculture. Constrained by the predictions from a validated kinetic model, DynamiCom consistently predicted the top metabolites being exchanged in the M-P coculture, as well as the establishment of the mutualistic N-exchange between the methanotroph and cyanobacteria. The interspecies interactions and their dynamic evolution predicted by DynamiCom are supported by ample evidence in the literature on methanotroph, cyanobacteria, and other cyanobacteria-heterotroph cocultures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Construct design for precise DNA insertion in plants

Precise insertion of DNA sequences at targeted locations in plant genomes is pivotal for synthetic biology, genetics, and crop improvement. Construct design plays a critical role in achieving precise insertions, yet practical guidance remains limited. This review provides an in-depth overview of construct design principles and targeted DNA insertion (knock-in) strategies in plants. We assess the strengths, limitations, and construct requirements of current knock-in methods for specific applications, including short, large, and multifragment insertions. Additionally, we explore the potential of adopting advanced nonplant technologies to enhance knock-in efficiency and precision in plants. This review provides a valuable resource for facilitating the effective application of knock-in technologies to genetically improve crops with minimal off-target effects.

DNA construct↗